International Journal of Web and Grid Services (13 papers in press)

Regular Issues

• Q-PD: query graph extension framework using predicate-based RDF clustering on linked open data (LOD)  
  by Jongmo Kim, Mye Sohn, Gyudong Park 
  Abstract: Linked Open Data (LOD) has emerged as a new platform for sharing and integrating information about not only web resources but also physical resources. However, as the volume of LOD increases explosively, it becomes difficult to query the LOD to discover the high-quality information. To obtain the desired information from the LOD, we propose the query graph extension framework (Q- PD framework) that can extend the users queries. To do so, the Q-PD framework identifies the Entity- Centered Graph (ECG), which contain the LOD resources directly related to the users queries. As a next, it performs predicate-based RDF clustering to find the topic graph patterns (TGPs), which are the ECGs to be reconstituted with information on the specific topics. Finally, the Q-PD framework extends the RDF graph patterns related to the users queries using the TGPs. To prove the excellence of the Q- PD framework, we performed the three kinds of experiment with 681.9 entities and 51577.1 RDF triples collected from DBpedia. Experimental results show that the Q-PD framework is superior to the existing bottom-up approach in terms of completeness and accuracy.
  Keywords: Semantic Web; Linked Open Data; Graph Clustering; Graph Pattern Recognition; SPARQL Query rewriting.
  
  
• Efficient Service Deployment in Mobile Edge Computing Environment  
  by Ao Zhou 
  Abstract: Mobile applications' requirements for compute capability grow up daily. Providing mobile service in remote cloud is one of the solutions to this issue. However, due to the long geographical distance of clouds, it is difficult to ensure the claimed performance of real-time service. As a result, mobile edge computing has become the main solution to solve this problem. The present researches are concerned with cloudlet placement, and computation offloading, while the problem about how to deploy services on cloudlets based on the user's geographical distribution is overlooked. We address this issue in our paper. With the consideration of minimizing the number of services and guaranteeing access delay constraint at the same time, this problem is formulated into an optimization problem. For the NP-hardness of the problem, an efficient heuristic algorithm is proposed to resolve it. The simulation experiment at the end of this paper evaluates the performance of this algorithm. Experiment results demonstrate that the proposed heuristic algorithm is effective.
  Keywords: edge computing; cloudlet; service deployment; delay.
  
  
• Analyze Resilience Risks in Microservice Architecture Systems with Causality Search and Inference Algorithms  
  by Kanglin Yin, Qingfeng Du, Juan Qiu 
  Abstract: The microservice architecture has already become the mainstream architecture pattern of web service applications in recent years. However, compared with traditional software architectures, the microservice architecture has a more sophisticated deployment structure, which makes it have to face more potential risks with greater diversity of fault symptoms. Microservice practitioners started to use the word "resilience" to describe the capability of coping with different unexpected conditions. How to judge whether a system environment disruption is a risk of microservice resilience, and how to analyze resilience risks before the system is released, are the research questions in microservice development. As the practice of chaos engineering has solved the problem of resilience risk identification, this paper focuses on how to analyze identified resilience risks in microservice architecture systems, and a resilience risk analysis method is proposed. Based on performance monitoring data collected during chaos experiments, the analysis method uses the causality search algorithm to build causality graphs of performance indicators, and generates causality chains to system operators by the causality inference algorithm. The effectiveness of the proposed approach is proved by conducting a case study on a microservice architecture system.
  Keywords: Microservice; Resilience; Software Risk Analysis; Causality Search and Inference.
  
  
• Self-Healing of Web Service Compositions: A specification rewriting approach  
  by Rafael Toledo, Umberto Costa, Martin Musicante, Genoveva Vargas-Solar 
  Abstract: We present an approach that improves the robustness of web service compositions enabling their recovery from failures that can happen at different execution times. We first present a taxonomy of failures as an overview of previous research works on the topic of fault recovery of service compositions. The resulting classification is used to propose our self-healing method for web service compositions. The proposed method, based on the refinement process of compositions, takes user preferences into account to generate the best possible recovering compositions. In order to validate our approach, we produced a prototype implementation capable of simulating and analyzing different scenarios of faults. Our work introduces algorithms for generating synthetic compositions and web services. In this setting, the recovery time, the user preference degradation and the impact of different locations of failure are investigated under different strategies, namely local, partial or total recovery. These strategies represent different levels of intervention on the composition.
  Keywords: Web Services; Self-Healing; User Preferences; Service Composition Rewriting.
  
  
• Formulating Monitoring Strategy based on Multiple SLA Parameters for Multi-tenant Service-based Systems  
  by Qian Chen, Zhiwei Ni, Yanchun Wang, Zhangjun Wu, Xuejun Li 
  Abstract: The widely used service-based systems (SBSs) are composed of individual services in the form of business processes and delivered to multiple tenants. When runtime anomalies occurred, the violation rate of Service Level Agreement (SLA) can increase remarkably. Therefore, service monitoring is crucial for meeting the tenant's Quality of Service (QoS) requirements. However, it is unrealistic to monitor each service constantly due to the limitation of monitoring resources. Its necessary to allocate monitoring resources according to services of different importance. Meanwhile, multi-tenant SBSs need to fulfill each tenants individual QoS requirements. In this paper, we propose a monitoring strategy based on multiple SLA parameters for multi-tenant SBSs (MMTS). The criticality of a service is evaluated to the importance of each service in a SBS based on two dimensions: QoS and tenants. Tenants are ranked by multiple SLA parameters, and their rankings are used for the calculation of service criticality. Afterwards, monitoring benefit, resource cost, and system overload are weighed to formulate a cost-effective monitoring strategy. Finally, MMTS is evaluated with comprehensive experiments under multiple QoS dimensions and the results have shown that MMTS can outperform other six algorithms in the SLA violation rate and the cost-effectiveness of service monitoring.
  Keywords: multiple tenants; service-based system; monitoring; criticality; Quality of Service; Service Level Agreement.
  
  

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.
  
  

Special Issue on: Service Platforms in Grid Computing – Recent Advances and Future Trends

• Unconstrained Temporal Inconsistency Checking of Natural Language in Webpage  
  by Lin Gan, Zhan Su, Shijun Li 
  Abstract: This paper discusses the problem called Web Temporal Inconsistency, which refers to the ambiguity and conflict between the time Webpages expressed and the actual time Web users concerned about and understanding in the current situation. It is an important criterion of quality evaluation of network information, related to the timeliness and accuracy of webpage content. Huge quantities of pages have the problem, seriously affecting the user's understanding of content and decision-making. This paper analyses the problem of Webpages, establishes the Temporal Inconsistency model and the method of measurement of Unconstrained Inconsistency which is one of the sub problems of Web Temporal Inconsistency, and constructs the reasoning mechanism based on the Web Time Axis. The Experiments show the model is superior to the baseline.
  Keywords: Unconstrained Inconsistency; Temporal Inconsistency Checking; Formal Natural LanguageWebpage Quality; Big Data; Services Computing.
  
  
• Energy consumption optimization based on mobile edge computing in power grid Internet of things nodes  
  by Hongbin Sun, Mingjun Liu, Zhejun Qin, Xiaofeng Li, Lixue Li 
  Abstract: With deployment and application of the power grid Internet of Things (IoT), all the nodes need more and more resources which bring a great challenge to the power grid system. Mobile edge computing (MEC) and rational use of renewable energy in the grid are effective way to solve above problem of grid resource allocation. In this paper, we propose a MEC framework and an offloading policy that considers renewable energy. The model fully considers the stochasticity of renewable energy arrival randomness and task offloading. By analyzing the renewable energy's dedicate character and adopt alternating direction method of multipliers (ADMM) algorithm, the method introduce a task computing offloading method based on renewable energy is proposed. The algorithm realizes the optimization strategy of the power grid internet node delay and grid energy consumption minimization. The simulation results show that the proposed algorithm performance exceeds the two baseline computation and offloading strategies, which can effectively optimize the grid energy consumption of the nodes.
  Keywords: Internet of things; power grid; renewable energy; optimization strategy; mobile edge computing.
  
  
• Resource scheduling of information platform for general grid computing framework  
  by Meihong You, Wenping Luo, Meizhang He 
  Abstract: In the information age, a large amount of data information generated every day not only brings a huge challenge to the processing and scheduling of information platform, but also promotes the emergence of a new information processing framework. The emergence and continuous development of grid computing provides new research ideas and development directions for system simulation and information platform resource scheduling. The corresponding concepts and calculation methods are very in line with the requirements of information platform resource scheduling. Based on this, this paper will discuss the related concepts of information grid in detail, which includes the key elements of grid computing. At the same time, it analyzes and studies the key technology of information grid, web services, and puts forward the framework of information grid for resource scheduling of information platform. In order to better realize the storage and management of information resources in the information platform, this paper innovatively proposes a meta database data storage and management algorithm for the integration of grid computing and cloud computing in the information grid environment, and designs the corresponding data management and storage framework. In order to reflect the advantages of the information platform resource scheduling in the framework and data storage management, this paper compares it with the cloud platform resource scheduling platform. The experimental results show that the framework system proposed in this paper has obvious advantages in improving the allocation efficiency of information resources and internal consumption per unit time, and also verifies the framework system in this paper Its advantages and practical application value.
  Keywords: Grid computing; Cloud computing; Information grid framework; Information platform resource scheduling; Database management algorithm.
  
  
• Green Lighting Intelligent Control System with Web Services Based on Back Propagation Algorithm  
  by Xiaokan Wang 
  Abstract: In order to solve the problems of large energy consumption in many stations, confusion lines and lighting source not accord with environmental protection requirement in the present,we put forward the scheme of automatic control system of green lighting based on PROFIBUS and PLC.In order to realize the inherent limitation of lighting control system in information sharing, remote control and other aspects, web services technology is combined with the original system to make full use of its technical advantages in distribution, openness and flexibility, so as to explore a better way for the development of industrial lighting network application.By constructing the communication network of the station lighting system with the PROFIBUS communication protocol and designing the hardware circuit and software program of the system bottom with programmable controller technology; simultaneously,the proposed BP neural network algorithm in the control system can realize intelligent control.Simulating with MATLAB of green computing for multimedia big data, the result shows that the station green lighting control system has very important significance of energy saving and provide the passenger for healthy, comfortable environment.
  Keywords: Green Lighting;Illumination Intensity;Web Services;Back Propagation Algorithm;Saving- energy.
  
  
• A Memory Based Task Scheduling Algorithm for Grid Computing Based on Heterogeneous Platform and Homogeneous Tasks  
  by Kunhao Tang, Wei Jiang, Ruonan Cui 
  Abstract: Grid computing is a new computing mode in recent years, which focuses on parallel infrastructure and its comprehensive application ability to network computers and distributed processors. Grid computing has been fully applied in the field of modern information technology and computer. Task scheduling is the core of grid computing. The quality of task scheduling algorithm directly affects the response time of the whole computing system. For heterogeneous tasks on heterogeneous platforms, this paper proposes a task scheduling algorithm with memory function, and introduces the distributed particle swarm optimization algorithm into this algorithm, which realizes the combination of resource processing tasks in grid computing and the behavior characteristics of intelligent groups, so as to better realize the dynamic and scalable scheduling of heterogeneous tasks on heterogeneous platforms to adapt to grid environment Sex. Finally, the grid simulation software GridSim is used to simulate the algorithm proposed in this paper. At the same time, it is compared with the state stochastic scheduling algorithm. Experimental results show that the proposed algorithm has obvious advantages in scheduling quality in grid environment.
  Keywords: Grid computing; heterogeneous platform isomorphic task;Memory function task scheduling algorithm;Distributed particle swarm optimization algorithm;Grid simulation;.
  
  
• Distributed Data Mining in Grid Computing Environment  
  by Jianlan Ren, Zhongsheng Chen, Zheng Zhang 
  Abstract: With the rapid development of computer technology, the data generated in the scientific research, industrial and commercial fields is increasing at an alarming rate. Traditional data mining techniques are limited to mining a single data source. How to mine distributed data sources and how to perform parallel mining is one of the hot topics in the field of data mining. The purpose of this article is to study distributed data mining in a grid computing environment. This paper studies the existing grid technology and data mining technology, and discusses the possibility of combining the two. Then based on this, a grid-based distributed data mining service framework is proposed, and the service framework is developed detailed design. This paper tests the framework, the experimental results show that applying the grid framework to distributed mining can improve the computing performance and data size. In this paper, the calculation speedup of the framework under 1 to 8 nodes is tested, and the speedup ratios are 1, 2, 3, 4, 5, 6, 7, and 8 respectively. It can be seen that the performance of the framework is directly proportional to the size of the calculation.
  Keywords: Grid Computing; Data Mining; Distributed Applications,Knowledge Discovery Framework; Web Service Resources.
  
  

Special Issue on: Web of Things (WoT) and its Intelligent Data Processing Services

• Data analysis of simulated WoT-based anti-crime scenario  
  by Chih-Chi Kuang, Kuei Min Wang, Lin Hui, Chuan-Yu Chang, Kuang Hui Chiu 
  Abstract: Police work is characterized by high risk and high cost. When a police task has no real-time information, the opaque situation could seriously compromise the success of the task. With the ap-pearance of the Internet of Things (IoT), it has become possible to create the smart things we need and to make them more effective. In addition, the Web of Things (WoT) has emerged recently. It enables us to integrate IoT more easily so that it can be applied to develop a specific system with a wireless sensor network (WSN) and platforms to perform specific tasks. This study proposes a methodology for examining the effectiveness of the WoT in support of the police work of freeing hostages held by terrorists. The proposed WoT-based police rescue squad force (RSF) concept was modeled and simu-lated using the developed Monte Carlo Simulation. The current and WoT-based RSF were the alternatives analyzed by simulation. The simulation results and t tests showed that there is a significant difference between the current and WoT-based RSF. The information gained from the simulation can support the police authoritys decision makers in upgrading the specific police information equipment with less risk, less cost and high effectiveness. The limitation is that the information from the study can only be used in the situation of hostage rescue tasks, i.e. it is inappropriate to apply it to other police work.
  Keywords: WoT; IoT; RSF; Simulation; Terrorist; UAV.