International Journal of Ad Hoc and Ubiquitous Computing (29 papers in press)
A Swarm Intelligence based Quality of Service aware Resource Allocation for Clouds
by Ashok Kumar
Abstract: The growing popularity of Cloud computing results in very large data centers around the world with vast amount of energy requirements and CO2 emissions. These large sized data centers demand efficient management of resources to conserve energy while satisfying Quality of Service (QoS) requirements of the end users. In this paper, a QoS-aware resource allocation approach using ant colony optimization is proposed. The proposed approach is implemented in CloudSim and comprehensive performance analysis shows upto 12% energy saving. rn
Keywords: Energy Efficiency;Resource Utilization;Resource Allocation;Swarm Intelligence; Quality of Service.
QoS-aware Flow Scheduling for Energy-Efficient Cloud Data Center Network
by Songyun Wang, Xiaoda Zhang, Jiabin Yuan, Zhuzhong Qian, Xin Li, Ilsun You
Abstract: It is highly valuable to achieve energy-efficient cloud data centers, which always act as the basic infrastructures. This paper thus aims at reducing the energy consumption of network devices in cloud data centers by flexible flow scheduling. For such an aim, it is necessary to guarantee the flow-level performance, which is a critical requirement for QoS (Quality of Service) in production data centers. Hence, this paper takes both energy reduction and QoS into account for flow scheduling, and then proposes a three-phase framework to control the energy consumption for cloud data center network (DCN) while guaranteeing flow-level performance. The proposed framework consists of three parts: flow rate estimation, flow path selection and flow rate allocation. The first part is done by exploiting TCP properties, which aims to guarantee flow-level performance. The flow path selection, based on the flow rate estimation, determines the switch states (on or off) to satisfy the rate requirements while accomplishing traffic proportional DCN energy consumption. Finally, we allocate the flow rates the links on the selected paths. From extensive simulations, it is shown that our solution could not only reduce about 20% of energy on average than the case with all switches on, but also maintain good flow-level performance, stability and fault tolerance simultaneously.
Keywords: Cloud Computing; Data Center Network; Energy Efficient; Flow Scheduling; Flow-level Performance.
Room measurement tool combining ultrasonic and inertial sensors in smartphones
by Yukitoshi Kashimoto, Yutaka Arakawa, Keiichi Yasumoto
Abstract: Obtaining accurate floor plans of buildings is critical for optimising indoor geographic information system (GIS) applications. In this paper, we present a room measurement tool that utilises a smartphone equipped with an ultrasonic sensor. To take measurements, users complete a lap along thewalls of all of the rooms. Then the tool accurately estimates the shape and size of them by tracking the walking paths of users and measuring the distance from the path to the walls with ultrasonic sensors. To track walking paths, we utilise inertial sensors embedded in the smartphone to estimate walking steps and turns, and the ultrasonic sensors to estimate the stride length when walking toward the wall. To account for such adjacent objects as bookshelves that decrease the accuracy of room size estimation, we used a mixed Gaussian filter. Our experimental results show that our tool considerably improved the estimation accuracy of the room shape and size.
Keywords: Room measurement tool; pedestrian dead reckoning; inertial sensor; smartphone;
Detection of Malware Applications using Social Spider Algorithm in Mobile Cloud Computing Environment
by Jannath Nisha O.S, Mary Saira Bhanu S
Abstract: Mobile devices have become an essential part of the daily routine of millions of users. The users run plenty of applications (apps) available in both the official market as well as unofficial application(app) market. Most of the mobile apps require resource-intensive computing power and software platform support for application execution. Many low-end but browser-enabled mobile phones are unable to support such apps. To bring adequate computational resources and storage to mobile apps, a technology named Mobile Cloud Computing (MCC) came into existence. In MCC, mobile apps are built, powered, and hosted using cloud computing technology. A mobile cloud approach enables developers to build applications designed specifically for mobile users without being bound by the mobile operating system and the computing or memory capacity of mobile devices. The attackers can also develop apps with malicious codes to perform malicious activities, such as privilege escalation, information stealing, monetization, etc. Although there are many security mechanisms available to scan and filter malicious apps, malware is still capable of reaching the user's mobile devices. So, security threats need to be considered before installing an app on a mobile device.
A large number of various types of features are available in an app to characterize its behavior. Among these, permission to access multiple resources by the apps is an important feature that can be used for detecting malicious apps. The requested permissions are extracted from the apps and a list of unique permissions are created. In this paper, the proposed model uses Social Spider Algorithm (SSA) to select the optimal set of permission features and then employs various classification algorithms to detect malware apps. The performance of SSA is compared with other stochastic-based optimization algorithms, such as Particle Swarm Optimization, Gray Wolf Optimization, Fruitfly Optimization, and Gravitational Search Algorithm. The experimental results demonstrate that SSA with various classification algorithms produces high accuracy with a low False Positive Rate. In case of a balanced dataset, SSA with Random Forest gives an accuracy of 94.46% with a high recall of 90% and a low false alarm of 0.02%
Keywords: Malware and Benign applications; Social Spider Algorithm; Mobile Cloud services; Permissions; Feature selection.
LWE-CPPA: A Scheme for Secure Delivery of Warning Messages in VANETs
by Shahab Haider, Ghulam Abbas, Ziaul Haq Abbas, Fazal Muhammad
Abstract: Conditional Privacy Preserving Authentication (CPPA) schemes preserve privacy of nodes and authenticate warning messages in Vehicular Ad hoc Networks (VANETs). However, the existing key exchange processes are computationally expensive, which compel CPPAs to rely on temper proof devices with pre-installed keys. Moreover, transmission of messages occurs as plaintext, which provides an opportunity to adversaries to intercept and temper communication. Furthermore, CPPAs provide no means for dealing with blackhole attacks. In this paper, we present a novel Light-Weight Encryption-enabled CPPA (LWE-CPPA) scheme that introduces encryption in warning messages. The scheme starts with the exchange of unique symmetric keys among nodes by using our proposed variant of Diffie-Hellman algorithm. After successful key exchange, the scheme uses our proposed VANETs specific novel lightweight encryption algorithm to yield a strong cipher for protection of messages from adversaries. An authentication process follows message encryption that makes our scheme robust. Furthermore, LWE-CPPA provides protection against blackhole attacks by employing a predefined threshold for warning messages acknowledgment. Simulation results demonstrate that LWE-CPPA provides improved security with reduced computational and communication overheads as compared to eminent CPPA schemes.
Keywords: Vehicular Ad hoc Networks; Conditional Privacy Preserving; Authentication; Security; Warning message dissemination; Message encryption in VANET.
LTE-Indoor (LTE-I): A Novel PHY Layer Design for Future 5G Indoor Femtocell Networks
by Kuo-Chang Ting, Jung-Shyr Wu, Chih-Cheng Tseng
Abstract: Small cell technology such as Femtocell plays an important role in 5G heterogeneous network especially in the indoor environments. However, it is unreasonable that the design of the PHY layer in Femtocell networks follows that of the Macro-cell since the channel model used in indoor environments is entirely different from that used in urban or rural areas. To boost the PHY throughput of Femtocell network, LTE-indoor (LTE-I), a new PHY layer frame structure, is proposed to accommodate more symbols in a slot time as well as to adopt higher order modulations and narrower guard bands. Furthermore, through carrier aggregation (CA) techniques, the PHY layer throughput can be further booted as high as 18.2 Gbps. The proposed LTE-I frame structure also supports the Ultra-Reliable and Low latency Communications (URLLC) by making the subcarrier spacing wider to increase the symbol rate with almost no throughput loss.
Keywords: Cyclic Prefix; Delay Spreads; Femtocell; ISI (Inter-Symbol Interference); LTE (Long Term Evolution); PHY; LAA; Throughput; WLAN.
An Energy-efficient Low-SAR Pathfinding Mechanism for WBAN
by Tin-Yu Wu
Abstract: In Wireless Body Area Network (WBAN), sensors nodes are placed on, in or around the human body to gather bioinformation for medical purposes. However, energy efficiency remains a crucial problem for WBANs. Energy consumption determines the lifetime of a network and any node failure could cause network failure. In the medical context, network failure may significantly degrade system reliability and result in considerable packet loss that could be life-threatening. In this study, Dijkstra algorithm is adopted for pathfinding. According to each node's remainder power and weighted SAR value, our proposed mechanism can find the path with the lowest SAR to reduce the effects of electromagnetic radiation on the human body.
Keywords: WSN; WBAN; SAR; Dijkstra's Algorithm.
An improved certificateless two-party authenticated key agreement protocol for wireless sensor networks
by Lunzhi Deng
Abstract: Key agreement is an important way to achieve secure communication betweenrnthe two or more parties. In the past decade, wireless sensor networks (WSNs) have received great attention and contributed to the development of low-power sensor networks. In WSNs, sensor nodes are generally inexpensive, low-power devices with limited computing and storage capabilities. So it is very valuable to design a secure and efficient key agreement protocol for WSNs. Recently, Bala et al. (2016) put forward a certificateless two-party authenticated key agreement (CL2PAKA) protocol for WSNs and asserted that it is provably secure in the extended Canetti-Krawczyk (eCK) model. In this paper, by showing the concrete attack, Bala et als protocol was proved to be vulnerable againstrnthe type I adversary. In order to make up for the security flaws, an improved protocol is proposed. It does not require pairing operations and requires only five scale multiplication operations, so it is suit for WSNs
Keywords: Certificateless Cryptography; Key Agreement; Wireless Sensor Networks;rnSecurity; eCK Model.
Collaborative Data Acquisition and Processing for Post Disaster Management and Surveillance Related Tasks using UAV based IoT Cloud
by J. Sathish Kumar, Saurabh Kumar, Meghavi Choksi, Mukesh Zaveri
Abstract: Rescue and recovery operations are very critical for post disaster management. For post disaster management and surveillance activities, there is a need of acquiring the information about the ground situation through sensing or observing data and identify the locations, which is a challenging task. These data may be sensed or observed through different types of sensors deployed in the area of interest. This can be achieved through a collaborative way of data acquisition and processing. In this context, this paper introduces the framework for data acquisition based on collaborative processing using unmanned aerial vehicles and Internet of Things network. The major contribution of this work is that the real time test bed using actual UAVs and IoT devices for data acquisition, clustering of different sensors and devices deployed for it and localizing the sensors and different events or situations arising in the region of interest is detailed and demonstrated. The framework is evaluated using real test bed with drones (UAVs) and integrated with cloud platform in IoT-based environment for data storage of the acquired data for further analysis and effective decision making in disaster situations.
Keywords: Collaborative Processing; Post Disaster Management; Surveillance; Internet of Things; Unmanned Aerial Vehicle (UAV).
E-DSR: Energy-efficient routing for sensors with diverse sensing rates
by You-Chiun Wang, Shih-Wei Yeh
Abstract: Cluster-based routing is popularly used in wireless sensor networks (WSNs), where sensors are organized into clusters and cluster heads (CHs) are selected to compress and forward packets for other nodes. However, most of existing protocols implicitly assume that sensors produce data with the same speed. Due to event occurrence or application needs, sensors may have different sensing rates in practice. Some CHs may thus encounter serious buffer overflow and dispose of many packets. To conquer this problem, the paper proposes a protocol called Energy-efficient routing for sensors with Diverse Sensing Rates (E-DSR) to extend network lifetime and diminish lost packets. E-DSR divides the network into grids and selects one CH in each grid based on multiple factors such as its position, residual energy, and sensing rate, so as to improve energy efficiency on routing. Moreover, depending on traffic loads of CHs, E-DSR adaptively splits or merges grids to avoid buffer overflow or facilitate data compression, respectively. Simulation results verify that E-DSR significantly prolongs network lifetime and reduces the data loss rate, as compared with various routing protocols developed for WSNs.
Keywords: cluster; energy efficiency; routing protocol; sensing rate; wireless sensor network.
Cryptanalysis of Certificateless Authenticated Key Agreement Protocols
by Runzhi Zeng, Libin Wang
Abstract: In this work, we cryptanalyze two Certificateless Authenticated Key Agreement (CL-AKA) protocols, Bala et al. (2018) and Xie et al. (2019), which are recently proposed claiming provable security. Specifically, we show impersonation attacks against the two protocols with successful probability 1 in extended eCK model using at most two queries. Then the process of our cryptanalysis is abstracted to a general method for cryptanalyzing a specific class of CL-AKA protocols which we call linearly-expressible CL-AKA protocol. Our method suggest new security requirements of CL-AKA protocols
Keywords: Certificateless Public Cryptography; Certificateless Key Agreement; Authenticated Key Agreement; eCK Model; Extended eCK Model; Security analysis; Cryptanalysis; Without Pairing;.
Multi-Location Anywhere Astronomy Paradigm
by Ayodele Periola, Lateef Akinyemi, Srinu Sesham
Abstract: Capital constrained astronomy organizations find it challenging to construct telescopes. Strategies such as converting unused satellite communication earth stations have been proposed. However, the conversion strategy is not sustainable due to the limited number of available unused satellite communication earth stations. Therefore, a new low cost approach to access telescopes is needed. This paper proposes a synergy between radio astronomy and satellite television broadcasting. The paper proposes a software defined radio enabled multi-mode satellite-television terrestrial telescope. The proposed telescope aims to provide all-round access to telescopes for astronomy observations. The performance benefit of the proposed solution is investigated using system acquisition costs and angular resolution as performance metrics. The proposed system reduces acquisition cost is reduced by 32.5% on average. The angular resolution is enhanced by a minimum and maximum of 17.7% and 82.3% on average respectively.
Keywords: Low-cost telescopes; Radio astronomy observations; Software defined radio; Satellite television broadcast; Developing nations.
MAC layer congestion control techniques in Vehicular Ad Hoc Network: Survey and Qualitative analysis
by Swati Sharma, Sandeep Harit
Abstract: Vehicular Ad Hoc Network (VANET) has become a promising area in the research community because of its various applications in road safety, mobile infotainment, and traffic management. Each vehicle can exchange information regarding the current status of traffic flow and warning through Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) mode of communication. There is a high need for reliable communication to reduce the number of accidents, and to enhance road safety. So, it can be ensured using efficient congestion control techniques at the Medium Access Control (MAC) layer. The design of MAC layer protocols in VANET is a challenging task due to dynamic topology, frequent link breakage, limited bandwidth, and Quality-of-Service (QoS) requirements. In this paper, various congestion control schemes that are designed for the MAC layer of VANET are classified and discussed, which include Time-Division Multiple-Access (TDMA) based MAC protocols and Decentralized Congestion Control (DCC). TDMA MAC protocols divide the time into slots and one vehicle can access the medium at each slot. DCC is a cross-layer function at each layer of the Intelligent Transportation (ITS) station. This study discusses various benefits, limitations, and characteristics of the techniques mentioned above. Finally, qualitative comparison based on different parameters and research gaps that can be considered for future research is represented.
Keywords: VANET; congestion control; MAC layer; TDMA; DCC.
To Attack or Not To: An Evolutionary Game Model to Study the Dynamics of Selfish PUEA Attackers in Cognitive Radio Networks
by Amar Taggu, Ningrinla Marchang
Abstract: The current paradigm shift towards heterogenous wireless networks is being spearheaded by 5G technology in which Cognitive Radio Networks (CRNs) have evolved as a promising enabling technology. CRNs are built around the concept of utilisation of white space in the spectrum of licensed users whenever they are not using their bands. However, CRNs are susceptible to many security attacks. CRN-specific attacks include Primary User Emulation Attacks (PUEA) and Spectrum Sensing Data Falsification (SSDF) attacks, which are mainly carried out by selfish attackers with the intent of maximising the utilisation of the spectrum all by themselves. This current work is an attempt to use Evolutionary game theory (EGT) to study the dynamics of selfish SUs (PUEA) and normal SUs in a CRN. The game formulation and the analysis thereof, are conclusive and can help an SU decide as to which, among the two strategies, To Attack or Not To Attack, to use, for enjoying a higher payoff.
Keywords: Evolutionary Game Theory; Replicator Dynamics; Cognitive Radio Networks; Evolutionary Stable Strategy; PUEA.
Service-aware objective function with QoS for RPL routing
by Tsung-Han Lee, Lin-Huang Chang, Jiun-Jian Liaw, Chih-Lin Hu, Hung-Chi Chu
Abstract: The routing protocol for low power and lossy network (RPL), constructed according to the objective function (OF), is the standard for routing selection in low power and lossy networks (LLNs). Most schemes utilize the expected transmission count (ETX) as the routing metric for the next hop. Designing effective and efficient routing protocols in LLNs require the mechanism to meet the criteria of different applications or services. In this paper, we propose a service-aware OF with quality of service (SOF-QoS) mechanism which integrates received signal strength indicator (RSSI), energy consumption, and hop count metrics into RPL OF for path selection according to different services, such as normal data, video packets and emergency messages transmission in LLNs. The proposed SOF-QoS mechanism defines various weights with fuzzy logic for the next routing selection in response to each service. We conduct the simulation under different network topologies with static and mobile scenarios to analyse the performance of the proposed SOF-QoS mechanism and compare them with the traditional RPL schemes. The simulation result shows that our proposed SOF-QoS mechanism provides relatively better or superior performance with reliability than traditional ones for different services.
Keywords: Mobility; RPL; energy consumption; RSSI; hop count; QoS.
Higher Order Statistics of Cooperative Mobile-to-Mobile Relay Communications over Composite Fading Channels
by Caslav Stefanovic, Stefan Panic, Vladimir Mladenovic, Srdjan Jovkovic, Mihajlo Stefanovic
Abstract: The paper investigates mobile-to-mobile (M2M) dual-hop amplify-and-forward relay (AFR) communications in composite fading environments. We model composite fading signal as the product of Nakagami-m (Nm) and Gamma (G) random processes (RPs) in order to address multipath-shadowing scenario and derive novel, fast computing, closed form mathematical formulas for i.) probability density function, ii.) cumulative distribution function iii.) outage probability, iv.) average level crossing rate and v.) average fade duration. The integral form statistical expressions are directly approximated by Laplace approximation (LA) method and exponential LA method. Moreover, we extended the model to cooperative M2M relay communications with n parallel independent dual-hop AFR links with selection combining scheme (SCS) at reception. The obtained results are numerically presented in order to show the impact of multipath-shadowing severity sets of parameters on the proposed M2M system. The detailed comparison of exact and approximated numerical results is provided for all considered statistical measures.
Keywords: Composite fading; Laplace method; M2M; outage statistics; relay systems.
A Comparison of Two Blending based Ensemble Techniques for Network Anomaly Detection in Spark Distributed Environment
by Gagandeep Kaur
Abstract: The work done in this paper involves the use of Apache Sparks RDD structure for the detection of network based anomalies using distributed machine learning algorithms. Two blending based ensemble models, namely, Logistic Regression based Blending Ensemble and SVM based Blending Ensemble have been compared in terms of their total training time in a distributed environment and their detection accuracy rates. Nowadays the real time network traffic data is known to change its characteristic with time and therefore any machine learning model once trained cannot be used forever. It leads to an increase in the false alarm rate. To handle this process of concept drift we have used clustering. Two clustering algorithms, KMeans Clustering and Gaussian Mixture Model (GMM) based Clustering have been compared for their training times in a distributed environment. As level one learner of ensemble algorithm distributed Random Forest Classifier has been used. Training times of Random Forest with KMeans based Clustering and GMM based Clustering have been compared and based on detection accuracy KMeans was selected for clustering. Tests have been conducted on different machines by varying the number of executor cores to study time latency in a distributed Spark environment. An accuracy of 90 percent for KMeans based Random Forest (KMbRF) Classifier was achieved, whereas the accuracy of 85 percent was achieved for Gaussian Mixture Model based Random Forest (GMMbRF) Classifier. Logistic Regression (LR) and Support Vector Machine (SVM) have been used as second level learners and their results have been com-pared. Logistic Regression based Blending Ensemble with an accuracy of 93 percent and an accuracy of 98 percent using SVM based Blending Ensemble was achieved. The proposed models have been evaluated using CIDDS Dataset.
Keywords: Resilient Distributed Data structures; Apache Spark; Clustering; KMeans; GMM; Random Forest; Ensemble; Anomaly Detection.
An Adaptive Minimum-Maximum Value based Weighted Median Filter for Removing High Density Salt and Pepper Noise in Medical Images
by Bharat Garg
Abstract: This paper presents an adaptive minimum-maximum value based weighted median (AMMWM) filter that effectively restores noisy pixel in medical images at high noise density. The proposed filter computes two highly correlated groups of noise-free pixels using minimum and maximum value of the current window. Further, weighted medians of these groups determine the estimated value of candidate noisy pixel. If the current window fails to provide any noise-free pixels, its size is increased by one. The maximum size of window considered is 7X7 to minimize blurring. The proposed AMMWM filter is evaluated on various medical images where it provides higher quality metrics while preserving image features even at higher noise density. The simulation results using X-ray images show on an average 0.3 dB and 3.56 dB higher value of PSNR for wide (10% - 90%) and very high (91% - 98%) noise density ranges respectively.
Keywords: Salt-and-Pepper Noise; Median Filter; Mean Filter; Non-linear Filter; Image Processing.
Nash Bargaining and Policy Impact in Emerging ISP-CP Relationships
by Hamid GARAMANI, Driss AIT OMAR, Mohamed El Amrani, Mohamed Baslam, Mostafa Jourhmane
Abstract: "Net neutrality" is the subject of raging debates for several years now, with various viewpoints put forth by stakeholders (Internet Service Providers, Content Providers, and end-users) seeking to influence how the Internet is regulated. With the network neutrality debate, the revenue sharing between Internet service providers (ISPs) and content providers (CPs) has been received attentions. In this paper, we study the revenue sharing of them through economic modeling, illustrating how monetary flows among providers are determined. There are generally two ways for CPs to get revenue: (i) charge users for the contents they view or download; (ii) get revenue from advertisers. On the other hand, Internet service providers (ISPs) are investing in network infrastructure to provide better quality of service (QoS). We investigate the mutual interaction of the service provider and content provider in two cases: (i) competitive case, where the ISP charge CPs for delivering content to end-users; and (ii) cooperative case, where the two providers (CP, ISP) jointly optimize their strategies, with the purpose of maximizing their aggregate profits. We formulate the interactions between the ISPs and between the CPs as a non-cooperative game in which the ISP and CP determine how much they will charge the end-users. In turn, the subscribers demand for the service of a provider depends not only on their strategies, but also upon those proposed by all of its competitors. We utilize bargaining games to analyze how the side payment between CP and ISP is determined. The sufficient and necessary condition for the existence and uniqueness of Nash equilibrium are derived. Based on the best response dynamics method, we propose a distributed iterative algorithm, starting from any initial strategies vector and converge to that Nash equilibrium. Finally, through extensive simulations, it has been verified that the cooperation is the best choice for three entities, i.e., the service provider, content provider and end-users.
Keywords: Network Neutrality; Nash Bargaining; ISP; CP; Nash equilibrium; game theory.
Simulated Annealing and Genetic Algorithm based Hybrid approach for Energy-Aware Clustered Routing in Large-Range Multi-Sink Wireless Sensor Networks
by KAVITHA ARUMUGAM, R. Leela Velusamy
Abstract: In recent years, the researchers have got progressively more interest in wireless sensor networks (WSNs) as it plays a vital role in numerous applications. WSNs have strict resource constraints such as limited bandwidth, limited energy, limited processing capability, and limited memory. Among them, the most critical one is limited energy. So, energy efficiency has got significant importance in the WSNs. Energy consumption is mainly due to computation and communication between sensor nodes and the base station. Energy consumption for communication is more when compared to computation. Hence it is indispensable to focus on designing an energy-efficient routing for WSN. In this paper, a cluster-based routing using Simulated Annealing and Genetic Algorithm based Hybrid (SAGA-H) approach has been proposed. The proposed approach is explained and simulated using MATLAB. Further, the results observed have been compared with existing GA based approach with respect to network lifetime, the number of packets sent to BS and sink, and average residual energy. From the simulation results, it is observed that the proposed approach outperforms the existing GA based approach.
Keywords: WSN; wireless sensor networks; clustered routing; energy aware routing; GA; genetic algorithm; simulated annealing; multi-sink WSN; energy efficient routing.
Popularity Prediction Caching Based on Logistic Regression in Vehicular Content Centric Networks
by Kai Yao, Zhaoyang Li, Lin Yao, Kuijun Lang
Abstract: To improve the network performance caused by mobility and sporadic connectivity in the vehicular network, Vehicular Content Centric Network(VCCN) is proposed by applying CCN into the vehicular network. The open in-network caching of CCN makes nodes cache contents cooperatively to facilitate information access. Tornimprove the network performance such as access delay and hit ratio, Road Side Units (RSUs) should try to cache more popular contents and provide better service for mobile users. This paper aims to propose a novel cache replacement policy - Popularity Prediction Content Caching (PPCC) for VCCN. In PPCC, we incorporate the future popularity of contents into our decision making. By learning the popularity of contents, we propose a cache replacement method based on logistic regression for RSUs in order to store those frequently access contents. The input data are related to the inherent characters of the received interests and the output is the predicted content popularity which guarantees that only popular contents are cached in the network infrastructures (i.e.RSUs). Simulation evaluations demonstrate that our scheme is very eective with higherrncache hit, lower access latency and higher caching eciency compared to other state-of-the-art schemes.
Keywords: VCCN; Cache Policy; Logistic Regression; Popularity Prediction.
An Enhanced Anonymous Authentication Protocol for Wireless Sensor Networks
by Jiping Li, Tong Yu, Yunyun Wu, Xia Kong, Shouyin Liu
Abstract: As a main component of IoTs, Wireless sensor networks (WSNs) are of greatrnimportance to data collection in varieties of sectors, such as environment monitoring, health monitoring of human body, farming, commercial manufacture, reconnaissance mission in military, and calamity alert, and so on. However, the nature of its wireless communication and resource constrain make it more likely to suer various kinds of attacks. As to this problem, many authentication s have protocols been designed recently to ensure secure communication in WSNs. Among the schemes, Singh et al.'s protocol shows great novelty. Unfortunately, we nd in our current research that Singh et al.'s protocol still has the vulnerabilities to stolen/lost smart card attacks, privileged-insiderrnattacks, the session key leakage attacks, and so on. To solve these problems, we propose an ecient anonymous authentication protocol by using hash function and bitwise XOR operations based on the security analysis of Singh et al.'s protocol. Secondly, we conduct detailed analysis to our protocol's security, and then security-feature comparisons with related protocols. In addition, we give formalized security proof of our by using Burrows-Abadi-Needham (BAN) logic. Finally, we give performance comparisons in regard to computing costs and communicating costs, respectively. Comparative summaries demonstrate that our protocol is much better in security with little overheads increase,rnand more appropriate for WSNs with limited resources.
Keywords: Authentication; Anonymity; Internet of Things; Key Agreement; BAN Logic.
Fine-Grained Emotion Recognition: Fusion of Physiological Signals and Facial Expressions on Spontaneous Emotion Corpus
by Feri Setiawan, Aria Ghora Prabono, Sunder Ali Khowaja, Wangsoo Kim, Kyoungsoo Park, Bernardo Nugroho Yahya, Seok-Lyong Lee, Jin Pyo Hong
Abstract: The recognition of fine-grained emotions (i.e. happiness, sad, etc.) has shown its importance in a real-world implementation. The emotion recognition using physiological signals is a challenging task due to the precision of the labelled data while using facial expressions is less appropriate for the real environment. This work proposes a framework for fusing physiological signals and facial expressions modalities to improve classification performance. The feature-level fusion (FLF) and decision-level fusion (DLF) techniques are explored in this work to recognize 7 fine-grained emotions. The performance of the proposed framework is evaluated using 34 subjects data. Our result shows that the fusion of the multiple modalities could improve the overall accuracy compared to the unimodal system by 11.66% and 13.63% for facial expression and physiological signals, respectively. Our work achieved a 73.23% accuracy for 7 emotions which is considerable accuracy for the spontaneous emotion corpus.
Keywords: Emotion recognition; Low sampling rate; Multimodal fusion; Spontaneous facial expression.
A selective forwarding technique for data dissemination in vehicular ad hoc networks based on traffic parameters
by Rangaballav Pradhan, Tanmay De
Abstract: In this work, a novel data dissemination technique is proposed based on the selective forwarding mechanism. Various network parameters such as node density,
inter-vehicular distance and time to leave are considered for choosing the appropriate relaying node out of a set of one hop neighbouring nodes of the sender. Veins, a simulation framework combining the power of Omnet++ and SUMO, is used to simulate and test the proposed approach. Simulation results are obtained by considering various performance metrics and the effectiveness of the method is justified by comparing with two existing methods namely Selective flooding and a Unidirectional Flooding. The analysis of these results showed that the proposed method has a higher Packet Delivery Ratio and coverage rate with a throughput surplus of 15% and 29% more than that of selective and unidirectional flooding respectively. It also has a minimum delay and a lower collision rate than the two flooding based approaches.
Keywords: VANETs; data dissemination; flooding; Selective forwarding; vehicular parameters; time to leave; vehicular density; Veins.
An Adaptive and Cooperative MAC Protocol in Vehicular Adhoc Network: Design and Performance Analysis
by Duc Ngoc Minh Dang, Quynh Ngo, Quan Le Trung, Long Le
Abstract: Vehicular Adhoc Network is the key technology to enable the Intelligent Transportation System. VANET should provide reliable broadcasting to support the safety-related application. It is also required to effectively transmit service-related data. With the rapid development of the Internet of Vehicles, Medium Access Control (MAC) protocols for VANET are expected to be more adaptive and scalable to the network size; so that the MAC protocol can operate effectively in supporting the massive number of connections. This paper proposes a multi-channel MAC protocol, namely AC-MAC, that enables multi-hop transmission of safety application data leveraging cooperation among vehicles. The proposed MAC protocol ensures the reliability of safety message transmission and the effective utilization of channel resources. Moreover, the MAC mechanism also has the ability to adapt to different network conditions.
Keywords: VANETs; IoTs; Multi-channel MAC; TDMA; CSMA; multi-hop; adaptive; cooperative.
A Channel Assignment Scheme for MIMO on Concentric-Hexagon-based Multi-Channel Wireless Networks
by Fang-Yie Leu, Heru Susanto, Kun-Lin Tsai, Chia-Yin Ko
Abstract: In a wireless network environment, multi-hop communication performed on a single channel may lead to hidden node and radio signal interference problems which are also the key reasons why network transmission efficiency is often not as expected. In fact, the hidden node problem is caused by radio signal interference, i.e., signal interference is the primary reason. Currently, numerous studies have used multi-channel schemes to solve the single channel interference problem. In general, Multi-channel can increase network capacity. However, it causes other problems, e.g., multi-channel hidden terminal/node problem and the issue about how to allocate channels to wireless nodes. Basically, a well-defined channel assignment can avoid radio interference and improve transmission performance. Therefore, in this study, we proposed a multiple channel assignment scheme, called Concentric-Hexagon-Oriented Multi-channel Assignment (CHOMA for short) which is suitable for use in a metropolitan-scale wireless network system with multi-input multi-output (MIMO) antenna, and the deployed eNBs are organized as concentric-hexagon (C-hexa for short). Available channels are grouped and then allocated to the C-hexas. We also arrange channels allocated to a C-hexa so as to reduce radio interference among its eNBs, consequentially improving the transmission capability and performance of a wireless network. Experimental results show that the CHOMA is really an interference-free scheme, no matter whether the target system is a network with SISO, SIMO, MISO or MIMO stations.
Keywords: wireless networks; eNB;signal/frequency interference; hidden terminal problem; multi-hidden terminal problem; channel allocation; MIMO.
Special Issue on: Artificial Intelligence for Edge Computing in the Internet of Things
Application of Artificial Intelligence Technology in CNC System
by Chunhui Dong, Cheng Zhong
Abstract: Since the development of computer numerical control technology from hardware numerical control to software numerical control, computer numerical control technology is still in a period of continuous improvement of functions. Although some novel numerical control technologies have been proposed, on the whole, it has not yet broken through the traditional framework. And because of the reliability research process of CNC machine tools, it is difficult to collect reliability data, which makes the reliability distribution model not unique. Based on the above background, the purpose of this article is to study the application of artificial intelligence technology in numerical control systems. The main method is to use the ANN model to expand the small amount of reliability data collected, and then use the Since the development of computer numerical control technology from hardware numerical control to software numerical control, computer numerical control technology is still in a period of continuous improvement of functions. Although some novel numerical control technologies have been proposed, on the whole, it has not yet broken through the traditional framework. And because of the reliability research process of CNC machine tools, it is difficult to collect reliability data, which makes the reliability distribution model not unique. Based on the above background, the purpose of this article is to study the application of artificial intelligence technology in numerical control systems. The main method is to use the ANN model to expand the small amount of reliability data collected, and then use the KS test to analyze the expanded data to determine the reliability data model. At the same time, in the process of determining the parameters of the reliability distribution model, the mixed Particle Swarm Optimization (HPSO) algorithm is introduced into the maximum likelihood estimation to solve the problems of easy to fall into the local optimal solution and low efficiency when solving some complex distribution models with small sample data. The experimental results show that the reliability distribution model of CNC machine tools is not unique in the case of a small sample. The reliability model of CNC machine tools can be uniquely determined after analyzing the data using the ANN model and the KS test method. Achieve a good balance between solution efficiency and convergence performance. Comparing the results of all the solving models, the relative mean square error of the 2-fold 3-parameter Weibull distribution after the ANN model expansion is the smallest, with a value of 0.0428, which shows that using this method to solve the reliability distribution model of CNC machine tools is feasible and can obtain More accurate results.
Keywords: CNC Machine Tools; Artificial Intelligence; ANN Model; HPSO Algorithm.
Special Issue on: Machine Learning and Deep Learning Methods for the Applications in Ad Hoc and Ubiquitous Computing
An Adaptive Stochastic Central Force Optimization Algorithm for Node Localization in Wireless Sensor Networks
by Pei-Cheng Song, Shu-Chuan Chu, Jeng-Shyang Pan, Tsu-Yang Wu
Abstract: Node localization in wireless sensor networks is a common and important practical application problem. Among the many localization algorithms, the MDS-MAP algorithm is a more effective one. However, the positioning effect of the MDS-MAP algorithm is not accurate in some cases, so the metaheuristic algorithm is implemented to further optimize the estimation results of the MDS-MAP algorithm in this paper. The improved central force optimization algorithm uses adaptive parameters to achieve randomness, while adding the restart strategy and accelerate strategy so as to avoid getting stuck in a local optimum. The CEC2013 and CEC2014 benchmark test suites used to verify the proposed algorithm are more competitive than some other existing algorithms. The improved central force optimization algorithm is applied to the MDS-MAP localization algorithm. The experimental results show that the improved central force optimization algorithm has a further optimization effect on the position estimation results of MDS-MAP.
Keywords: Central Force Optimization; Restart strategy; Adaptive; Stochastic; MDS-MAP; WSN.
A Compact GBMO Applied to modify DV-Hop based on layers in wireless sensor network
by Jeng-Shyang Pan, Min Gao, Jian-po Li, Shu-Chuan Chu
Abstract: Gases Brownian Motion Optimization (GBMO) has been shown a useful optimization method. The compact concept is implemented to the GMBO named Compact Gases Brownian Motion Optimization (CGMBO) so as to improve the efficiency and effectiveness of the GMBO. Simulation results based on the 23 test functions consisting of the unimodal, multimodal, fixed-dimensional functions and composite multimodal functions demonstrate the superior of the proposed CGMBO. The idea of layer concept is also proposed to implement the Distance Vector-Hop (DV-Hop) by modifying the original average distance of each hop called Layer DV-Hop (LDV-Hop), experimental results also show the proposed LDV-Hop really improve the average positioning accuracy of each node for wireless sensor network. Finally, the proposed CGMBO is combined with the proposed LDV-Hop so as to greatly reduce the position error compared with the DV-Hop. The actual error per-hop distance between nodes is large. When the calculated average hop distance of the nodes does not reach the ideal value, the actual distance between the nodes and the calculated distance will have a large deviation.
Keywords: Gases Brownian Motion Optimization; Wireless Sensor Network; Compact Gases Brownian Motion Optimization; LDV-Hop.