International Journal of Web and Grid Services (16 papers in press)
Real-time Adaptive QoS Prediction Using Approximate Matrix Multiplication
by Marin Silic, Adrian Kurdija, Sinisa Srbljic
Abstract: We introduce a novel QoS prediction model as a real-time support for selection of atomic service candidates based on their QoS properties while constructing composite applications. The proposed approach satisfies the following requirements: (i) fast and accurate prediction of QoS values, and (ii) adaptability with respect to environment changes. The model precomputes the similarities between users and services using approximate matrix multiplication to reduce the time complexity. When calculating a prediction for a user-service pair, the model considers similar users and services, but enhances the prediction accuracy by incorporating the number of observed records. Time complexity is further reduced by storing the lists of similar users and services which are updated in real-time. The model adapts to the changing environment: newer records are set to have greater influence on the predictions. The experiments conducted on relevant service-oriented datasets show advantages of the proposed model in accuracy and time performance.
Keywords: web services; quality of service; QoS prediction; service recommendation; real-time adaptability; approximate matrix multiplication.
PSPO: A Framework for Cost Effective Service Placement Optimization during enterprise modernization on Hybrid Clouds
by Ravikumar Ramadoss, N.M. Elango, A. Satheesh, Ching-Hsien Hsu
Abstract: An integrated cloud service model utilizing both public and private cloud services to provide a holistic deployment of the enterprise applications is the need of the hour. Adopting hybrid cloud during enterprise modernization delivers cost effective option and secured performance. Traditional existing applications getting modernized to meet the high business demands to serve various sets of end customers, with its technology enhancements adapting to big data and cloud to achieve the futuristic SLA. In this paper, we proposed a proactive cost optimization model during various service placements by considering modernization characteristics on multiple clouds. The proposed algorithm solves some of the key issues towards datacenter, environment, licenses and enterprise modernized transactions. Experimental results derived shown that the proposed work optimizes the parameters required for effective service placement.
Keywords: Cost factors; Enterprise modernization; Hybrid clouds; Service migration.
Emerging Issues and Challenges for Cloud Data at the Edge
by Kok-Seng Wong, Myung Ho Kim
Abstract: Due to advantages such as flexibility, mobility, and cost-saving, the pushing of data storage and processing into the cloud has been a key trend in many enterprises. Recently, researchers have found that there is a growing limitation in the meeting of the computing and network bandwidths for the cloud when supported systems such as the Internet of Things (IoT) are used. Instead of establishing channels for the cloud storage and utilization, edge-centric computing places some of the processes and resources near to the users; however, its utilization has raised security concerns about the data usage, and the existing secure mechanisms in the cloud are no longer suitable for data protection at the edge. In this paper, the security issues of cloud data at the edge are studied. We present several challenges and opportunities for edge computing and demonstrate the impact of privacy leakage in IoT applications.
Keywords: Edge-centric computing; secure data sharing; fog computing; data privacy protection; IoT applications.
Performance Modeling and Analysis for IoT Services
by Jiwei Huang, Songyuan Li, Ying Chen, Junliang Chen
Abstract: With the growing popularity of Internet of Things (IoT) services on the Internet, performance has become an important issue in the design and optimization of IoT services systems. This paper proposes a theoretical approach of performance evaluation for IoT services, which is expected to provide a mathematical prediction on performance metrics at the design phase before system implementation. In specific, we firstly formulate an atomic service by a queueing system, and then an IoT system can be modeled by a queueing network. Detailed quantitative model analyses under different request arrival distributions are presented, and performance metrics are obtained. Furthermore, we briefly study two popular problems which are resource management and task scheduling in order to illuminate how the models and analytical results can be applied in the design and optimization of IoT systems. Finally, real-world data based simulation experiments are conducted to validate the effectiveness of our approach.
Keywords: Performance Evaluation; Internet of Things (IoT); IoT Service; Quality of Service; Queueing Model.
One Size Does Not Fit All: Logic-based Clustering for On-the-fly Web Service Composition and Verification
by Khai Huynh, Tho Quan, Thang Bui
Abstract: Recently, Web Service Composition (WSC) has been widely emerging since it is obviously hopeless to develop a specific web service which can single-handedly fulfill completely a requirement previously posed by clients. Moreover, as a WSC solution often needs to satisfy various kinds of constraints, its correctness is also required to be formally verified. However, composition and verification tasks always suffer from huge computational cost when applied in practice. It prompts the consideration of clustering approaches, which group similar web services into same clusters for further processing. Unfortunately, typical clustering techniques cannot ensure that all of the web services grouped into a cluster fulfill a certainly required constraint. Likewise, those techniques do not also guarantee that all of the web services fulfilling a constraint will be put into the same cluster. In other words, the existing web service clustering approaches accomplish neither the soundness nor completeness of a composition solution.
To overcome this problem, we propose a logic-based approach for clustering web services, where logic formulae are used for representing web services and their clusters. The clustering results are then further applied for WSC and verification in an on-the-fly manner. In the theoretical aspect, our approach achieves both soundness and completeness. In practice, the logic-based similarity used in our approach generates more reasonable clusters, resulting in significant performance improvement in experimentation.
Keywords: Logic-based Web Service Clustering; Logic-based Web Service Similarity; Web Service Clustering; Web Service Composition; Web Service Formal Definition.
G-OPTICS: Fast Ordering Density-based Cluster Objects using Graphics Processing Units
by Wookey Lee, Woong-Kee Loh
Abstract: Clustering is the process of forming groups or clusters of similar objects in the dataset and has been used as an important tool for many data mining applications including the web-based ones. While density-based clustering algorithms are widely adopted, their clustering result is highly sensitive to parameter values. The OPTICS algorithm presents a solution to this problem; it produces an ordering of objects that is equivalent to the clustering results for a wide range of thresholds e. In this paper, we propose an algorithm named G-OPTICS to significantly improve the performance of OPTICS using a Graphics Processing Unit (GPU). The experimental results using real and synthetic datasets demonstrated that G-OPTICS outperformed the previously fastest FOPTICS algorithm by up to 118.3 times (67.7 times on the average).
Keywords: ordering of objects; density-based clustering; graphics processing unit; parallel algorithm.
Implementation and Evaluation of Hybrid Broadcasting System for Webcasts
by Takeshi Ozaki, Yusuke Gotoh
Abstract: Due to the recent popularization of grid environments, streaming delivery using broadcast and telecommunication method systems is attracting great attention. In streaming delivery under hybrid broadcasting environments, clients concurrently receive such streaming data as music or movies from both broadcasting and telecommunication systems. Although these systems compensate for their respective the demerits, the waiting time is lengthened if the system does not deliver the data efficiently. To reduce this waiting time, many researches have proposed scheduling methods. However, since most scheduling methods use a computer simulation, they do not clearly show their the effectiveness. In this paper, we design and implement a hybrid broadcasting system to solve the problems of conventional methods. In our proposed system, we evaluate how efficiently they reduce waiting times using scheduling methods.
Keywords: Hybrid broadcasting; Continuous media data; Scheduling; Waiting time.
Blockchain Challenges and Opportunities: A Survey
by Zibin Zheng, Shaoan Xie
Abstract: Blockchain, the core mechanism in Bitcoin, has received extensive attentions recently. Blockchain serves as a public ledger and transactions stored in blockchain are nearly impossible to tamper. Blockchain has the key characteristics such as decentralization, persistency, anonymity and auditability. Blockchain help to improve efficiency and security. It could be applied into many fields including financial services, reputation system and public services. However, there are still a large number of technical challenges prohibiting the wide application of blockchain: scalability problem, privacy leakage etc. This paper presents a comprehensive survey on blockchain technology. In this paper, we present a comprehensive survey on the state-of-the-art research efforts on blockchain technology. In particular, we first give an overview on blockchain technology. The typical blockchain consensus algorithms are then introduced. We next present a survey on blockchain applications and technical challenges as well as recent advances. Finally, future research directions are also discussed.
Keywords: Blockchain; Decentralization; Consensus; Application.
Efficient Request Assignment Algorithm in Mobile Cloud Computing Environment
by Ao Zhou
Abstract: Recently, mobile applications have become increasingly computation-intensive. However, the energy and the computing capabilities of mobile devices, such as smartphones and tablets, are limited. Mobile cloud computing is becoming a powerful way to tackle this challenge. Offloading computation-intensive tasks to nearby cloudlets can significantly save energy and enhance the computation capabilities of mobile devices. However, determining how to assign task requests to cloudlets while minimizing the response time remains a challenging issue. The traditional approach cannot achieve the optimal effect since it ignores the task characteristics and the communication characteristic between the cloudlets. To address this challenge, in this paper, we provide an efficient algorithm for task request assignment that shortens the response time and reduces the network resource consumption. We first formulate the problem as a response time and network resource consumption minimization problem. To solve this problem, we then propose an optimized differential evolution algorithm. We finally evaluate the performance of the proposed task request assignment algorithm through experimental simulations. Simulation results demonstrate that the proposed algorithm is promising.
Keywords: Mobile cloud computing; Edge computing; Cloudlet; Request assignment.
PRE+: dual of proxy re-encryption for secure cloud data sharing service
by Xu An Wang, Fatos Xhafa, Jianfeng Ma, Leonard Barolli, Yunlong Ge
Abstract: In this paper, aiming at providing secure cloud data sharing services in cloud storage, we propose a scalable and controllable cloud data sharing framework for cloud users: Scanf. Towards proposing this framework, we introduce a new cryptographic primitive: PRE+, which can be seen as the dual of traditional proxy re-encryption (PRE) primitive. All the traditional PRE schemes until now require the delegator (or the delegator and the delegatee cooperatively) to generate the re-encryption keys. We observe that the encrypter also has the ability to generate re-encryption keys. Based on this observation, we construct a new PRE+ scheme, which is almost the same as the traditional PRE except the re-encryption keys generated by the encrypter. Compared with PRE, PRE+ can easily achieve the non-transferable property and message-level-based fine-grained delegation. Our Scanf framework based on PRE+ can also achieve these two properties, which is very important for cloud storage sharing service.
Keywords: dual of proxy re-encryption; message-level-based fine-grained delegation; non-transferable property; secure cloud data sharing service.
Searchable symmetric encryption based on the inner product for cloud storage
by Jun Yang, Shujuan Li, Xiaodan Yan, Baihui Zhang, Baojiang Cui
Abstract: Searchable encryption enables the data owner to store their own data after encrypting them in the cloud. Searchable encryption also allows the client to search over the data without leaking any information about it. In this paper, we first introduce a searchable symmetric encryption scheme based on the inner product: it is more efficient to compute the inner product of two vectors. In our construction, the parties can be data owners, clients or the cloud server. Three parties communicate with each other through the inner product to achieve the goal that client can search the data in cloud without leaking any information on the data the owner stored in the cloud. We then perform a security analysis and performance evaluation, which show that our algorithm and construction are secure and efficient.
Keywords: inner product; searchable encryption; searchable symmetric encryption; security; the cloud server.
Compromising location privacies for vehicles cloud computing
by Chi Lin, Yi Wang, Shuang Wei, Danyang He, Jie Wang
Abstract: In this paper, we propose an enhanced vehicular crowdsourcing localisation and tracking (EVCLT) scheme for mounting a trajectory tracking attack in vehicular cloud computing environment. In our scheme, crowdsourcing technique is applied to sample the location information of certain users. Then matrix completion technique is used to generate our predictions of the users' trajectories. To alleviate the error disturbance of the recovered location data, Kalman filter technique is implemented and the trajectories of certain users are recovered with accuracy. At last, extensive simulations are conducted to show the performance of our scheme. Simulation results reveal that the proposed approach is able to accurately track the trajectories of certain users.
Keywords: crowdsourcing; Kalman filter; matrix completion; trajectory tracking.
Data integrity checking with reliable data transfer for secure cloud storage
by Yong Wang, Xiaoling Tao, Jianbing Ni, Yong Yu
Abstract: Currently, an increasing number of data owners prefer to store their data on remote servers due to a number of appealing advantages of cloud storage, say convenience and simplicity, scalability of the service and ubiquitous network access. However, outsourced data's transfer becomes a critical requirement for cloud users because of the emergence of various cloud storage services with different qualities of services. Therefore, the users might not only be anxious about the status of their data on cloud servers but also care whether the data are transferred entirely to the new cloud without corruption and whether the data on original cloud are discarded. To address these challenging issues, in this paper, we propose a novel auditing scheme for cloud storage services characterised by secure data transfer, provable data erasure, high error detection probability, confidential data storage. The proposed scheme can guarantee the integrity of remote data when the data are hosted on cloud servers and are transferred between two clouds, and secure deletion of the transferred data on the original cloud.
Keywords: cloud storage; data integrity; data deletion; data transfer.
Special Issue on: Security for Cloud Computing
Lattice-based searchable public-key encryption scheme for secure cloud storage
by Run Xie, Chunxiang Xu, Chanlian He, Xiaojun Zhang
Abstract: With the improvement of awareness of data privacy, the user's sensitive data are usually encrypted before uploading them to cloud. Searchable encryption is a critical technique on promoting secure and efficient cloud storage. In particular, publickey encryption with keyword search (PEKS) provides an elegant approach to achieve data retrieval in encrypted storage. All existing searchable publickey encryption schemes only provide the security based on classical cryptography hardness assumption. With the development of quantum computers, these schemes will be insecure. Based on the lattice hardness assumptions, we propose a new searchable publickey encryption scheme with a designated tester (dPEKS). Our scheme has advantages: First, our scheme is the first searchable publickey encryption scheme that is considered to be secure even if quantum computers are ever developed. Second, our scheme achieves the trapdoor indistinguishability. The trapdoor indistinguishability implies the security against outside offline keyword guessing attacks (KGAs). Last, our scheme can achieve the trapdoor anonymity for server.
Keywords: cloud storage; keyword-guessing attack; lattice; searchable encryption; trapdoor indistinguishability.
Key-aggregate searchable encryption under multi-owner setting for group data sharing in the cloud
by Tong Li, Zheli Liu, Chunfu Jia, Zhangjie Fu, Jin Li
Abstract: In recent years, the encryption with keyword search has been widely used in cloud data sharing system to protect privacy and confidentiality when the ciphertext is retrieving. However, selectively sharing encrypted data and related searching abilities among different users via the existing searchable encryption technology certainly will generate a large number of searching trapdoors making the system inflexible and impractical. In this paper, we propose the concept of "multi-owner key-aggregate searchable encryption" scheme and its implementation, in which a user can only submit a trapdoor for querying the documents shared by multiple owners who only need to distribute an aggregate key for sharing massive data. Thus, the scheme supports effective data sharing for both multiple owners and users by reducing unnecessary trapdoors which are hard for generating by mobile devices during the querying step. Finally we conduct security analysis and performance evaluation which can show that our system is practical and secure.
Keywords: cloud storage; data sharing; key-aggregate; searchable encryption.
Special Issue on: Security for Cloud Computing
Searchable Symmetric Encryption Based on the
Inner Product for Cloud Storage
by Jun Yang, Shujuan Li, Xiaodan Yan, Baihui Zhang, Baojiang Cui
Abstract: Searchable encryption enables the data owner to store their own data after
encrypting them in the cloud. Searchable encryption also allows the client to search over
the data without leaking any information about it. In this paper, we rst introduce a
searchable symmetric encryption scheme based on the inner product: it is more ecient
to compute the inner product of two vectors. In our construction, the parties can be Data
Owners, Clients or the Cloud Server. The three parties communicate with each other
through the inner product to achieve the goal that the client can search the data in the
cloud without leaking any information on the data the owner stored in the cloud. We then
perform a security analysis and performance evaluation, which show that our algorithm
and construction are secure and ecient.
Keywords: Searchable Encryption; Searchable Symmetric Encryption; Inner Product;
the Cloud Server; Security.