Earticle

In order to solve the problems of ill-balanced task allocation, long response time, low throughput rate and poor performance, which appeared in cluster system, this paper proposes a new load balancing algorithm of homogeneous cluster based on the variation trend of entropy. In this paper, we introduces the thermodynamic concept of entropy into load balancing algorithm and gives a new algorithm, so that we can calculate the entropy of the system to ensure that each scheduling and migration toward the entropy increasing tendency. The result of simulating experiments shows that this algorithm has more obvious advantages compared with traditional algorithms, such as achieving the load balancing status as soon as possible, shorting the task execution time, increasing system performance and so on.

A new decentralized method is proposed to resource discovery in Grid computing systems. This agent-based method supports semantic description and is flexible for resource identification and allocation. It allows each of the individual resource agents to interact only with its neighbor agents semantically and form a resource chain for a specific task dynamically. We discuss about the success of probability of our method under different task loading rates and compare it with some other known Algorithms. The experiments show the algorithm could flexibly and dynamically discover resources.

WSN is often deployed in unattended or even hostile environments. Therefore, providing security in WSN is a major requirement for acceptance and deployment of WSN. Furthermore, establishing trust in a clustered environment can provide numerous advantages. We proposed a light-weighted trust model which consider data aggregation and detailed the data in parameters to depend against attacks. With comparing our model with LDTS and Model using Trust Matrix, we conclude that our model has implemented a trade-off between detection rate and communication consumption.

In the cloud computing environment, according to the predicting average response time of service, it can adjust to the follow-up system, so that the response time of the system is acceptable. The traditional methods of predicting average response time of serve mainly include the method of gray predicting and neural network model, but the two methods face several problems, such as longer processing time and unsuitable to larger volatility data. According to the above problems, the paper proposes the method of predicting average response time of cloud service based on the MGM (1, N) - BP neural network, the combination of two methods of predicting can use less sample information, it can get a high precision of predicting result and it can also predict the volatile system. Experimental results show the feasibility and effectiveness of the method.

In this age of data and knowledge, Cloud, Grid and P2P systems are becoming common and advanced. Due to heterogeneous and distributed nature, Grid becomes more vulnerable to faults. Trace files are great way of storing and collecting fault and workload information from the system. FTA (Fault Trace Archive) and GWA (Grid Workload Archive) are two such trace files. Previously FTA and GWA have been individually analyzed by researchers, but in this research paper for the first time, we have analyzed the combination of FTA and GWA as a single research problem. Trace files have been joined based on the event timestamp values. Both the trace files have been analyzed to establish a correlation based model among node failures, failed jobs, number of nodes and failure duration. We have discovered that these factors are positively correlated with each other but to a different extent. Along with node failure frequency, failure resume time and node dedication factor, we have found that interactive jobs have a higher failure probability as compared to batch jobs.

With the development of cloud computing, the number and types of cloud services experience an explosive increase. Towards improving the Quality of Service provided in cloud computing, we model cloud computing’s admission control in this paper. Based on the observation that cloud service requests are typically concurrent, we propose admission control method for aggregate flow by computing the its effective bandwidth using network calculus. Acceptance decision is consequently made by computation with the effective bandwidth. Experiments are conducted to investigate properties of effective bandwidth, and to evaluate the performance of the admission control method under different settings.

Cloud computing presents new security and privacy challenges to control access to multi-tenant applications in the cloud. However, this solution has more challenges once the number of access control list (ACL) increases in the cloud, such as efficiency of policy resolution, multi-tenancy and data isolation. To address these limitations, this paper describes a fine-grained data-level access control model (FDACM) suitable for multi-tenant applications where role-based and data-based access control are both supported. Lightweight expressions are proposed to present complicated policy rules in our solution. Moreover, we discuss the most important part of FDACM in detail: query privilege model and decision privilege model. Furthermore, we also propose the architecture and authorization procedure which implements these two models. Some technical implementation details together with the performance results from the prototype are provided. Finally, a case study of FDACM is illustrated to evaluate the effect of the application in practice.

Cloud computing is emerging as a powerful architecture to perform large-scale and complex computing. It extends the information technology (IT) capability by providing on-demand access to computer resources for dedicated use. The information security and privacy are the major concerns over the cloud from user perspective. This paper surveys and evaluates the architecture, data security and privacy issues in cloud computing like data confidentiality, integrity, authentication, trust, service level agreements and regulatory issues. The objective of this paper is to review comprehensively the current challenges of data security and privacy being faced by cloud computing and critically analyze these issues.

In Wireless Sensor Networks (WSNs), as the network consists of low-cost sensor nodes with finite battery power, power efficient strategies must be applied for data transmission in order to prolong the lifetime of the network. It is important to minimize the total energy consumption in each round so that the network lifetime is maximized. In this study, we propose a new energy efficient protocol E-CTP based on the Collection Tree Protocol (CTP). Taking into account the power available to the whole network and single node, the Expected Transmission Value (ETX) was updated according to the proposed protocol. The related experiments were carried on TelosB, the results were compared in terms of lifetime and efficiency. We conclude that the new protocol has a longer lifetime and higher efficiency.

With the rapid development of communication technology and mobile Internet, selecting from mass Location-based Services to meet the needs for different users becomes the research hot spot under mobile Internet environment. First of all, it starts from QoS constraints as well as user preferences in this paper, and then describes a mobile service selection framework based on QoS constraints and user preferences. Furthermore, a User Preferences Database is built in modeling user preferences by Similarity Formula. Users’ feedback is adopted to update User Preferences Database, which makes the combination between QoS constraints and user preferences more compact. Then, a LBS selection model and algorithm are proposed separately, which considers the QoS attributes and user preferences. Finally, it takes Online Learning Resources Platform (OLRP) based on mobile terminals as a sample, and designs a mobile course resources selection system on campus. The results show that the proposed algorithm is precision and effective in solving the problem of service selection to support Location-based Services personalization.

Cloud Computing is evolving as a key computing platform for sharing infrastructures and applications with flexible scalable computing processing power. Virtualization is a core technology for enabling cloud sharing ability. The management of cloud core infrastructure is essential to provide cloud computing environments. And the management, monitoring, and configuring of network from the cloud is another key topic in this paper. This paper presents a new management model architecture named MulCNeT(Multi-tenant, Cloud-based, Network Property trusteeship ). A system, which has been developing based on this architecture, is introduced. The architecture is based on cloud model, focusing on monitoring, configuring, and managing network with property management business model.

Evaluating the hot degree of VM (Virtual Machine) is the critical link of the VM hotspot eliminating process. Based on the traditional research, this paper creates hot degree evaluation system combining VM service availability and service quality factors. It proposals the subjective weight algorithm based on fuzzy analytic hierarchy process and the objective weight algorithm based on maximum deviation, and hot degree comprehensive evaluation method based on these two weights. A rule of VM cold-spot or hotspot evaluation based on hot degree is presented. The experiment result indicates the accuracy of the method in this paper is higher than traditional approaches to evaluate the hot degree, which can efficiently reduce improper migration, with smaller price.

Lightweight Mashup service become very prevalent now since there are lots of advantages for them, such as easy use, short development time, and strong scalability. It is a challenge problem how to recommend user-interested, high-quality Mashup services to user with the rapid development of more and more Mashup service. In this paper, we propose CSCF (a Mashup service recommendation approach based on Content Similarity and Collaborative Filtering). CSCF firstly computes the content similarity between user history records and Mashup services and gets user interest value. Secondly, according to Mashup QoS(Quality of Service) invocation records of user, user similarity model and service similarity model are designed, and then get the QoS prediction value of active user to target service by using collaborative filtering. Finally, combining user interest value and QoS predictive value of Mashup service, CSCF ranks and recommends Mashup services to user. The experiments are performed with real Mashup services dataset, and the results of experiments show that CSCF can effectively recommends Mashup services to user with well-interesting, high-quality, better prediction precision.

We focus on the problem how to achieve network lifetime extension without causing serious deteriorated on network performance. A cooperative E-ARP protocol for extending network lifetime in wireless AD Hoc networks is proposed in our paper. By means of piggyback, energy information exchanges among neighbors in our scheme, which makes a little modification to traditional ARP protocol. E-ARP protocol can carry energy information of wireless nodes, which decreased the risk of communication resource competition between ARP information and exchanging energy information. It also allows the node with sufficient energy to help multiple nodes at one time, thus the extra communication workload can be decreased. In evaluations chapter, the simulation results show that E-ARP protocol can achieve an almost similar performance on lifetime extension with the known method CTCA but better network performance.

SGIT(Interactive Terminal of Smart Grid) access to the intranet of electric power information, expanding the boundaries of network protection and bringing in risks of security. Based on safe requirement and trust computing theory, TCM(Trust Cryptographic Module) and TAS(Trust Access Server) are introduced to Interactive terminals and boundary of information network respectively. Trusted operating environment, trusted identity and credible communication are ensured through the cooperative work of TCM and TAS, which makes terminals be accessed credibly. The emphasis is the remote attestation model and trusted authentication protocols based on the verifier. The analysis of this mechanism was made, which indicates that this mechanism can make sure the credible access of SGIT and has practical application value.