This article describes the capability of online data storage which has been enhanced by the emergence of cloud datacenter development. Distributed Hash Table (DHT) based image retrieval system using locality sensitive hash (LSH) has provided an efficient way to set up distributed Content Based Image Retrieval (CBIR) frameworks. However, with the fixed LSH function adopted, LSH and other codebook-based distributed retrieval systems are facing the problem of flexibility, and also are difficult to satisfy the user's demand. In this article, LRFMIR is proposed to introduce semantic search into DHT based CBIR system. LRFMIR is established on a DHT based network, where a flexible result truncating strategy is employed to fuse provided results by using multiple features measurements. Experiments show that LRFMIR provides a higher accuracy and recall rate than single feature employed retrieval systems, and possesses good load balancing and query efficiency performance.

Cloud-based big data platforms provide physical resources for a variety of applications to analyze all forms of data. For the stream big data analytics, a participated task always needs to scale out resources when its input data increases steeply. Typically, the resource scaling out can be achieved by increasing the parallelism degree of the platform based on the experience. However, the resource scaling-out of each task produces additional cost not only from itself but also from other competitive tasks, which brings about great challenges to ensure the efficient utilization of resources. To solve this problem systematically, we consider the resource scaling-out problem as a non-cooperative game and formulate a total cost model including a risk function and a task execution time function. The total cost of resource scaling-out reflects the influence of topology structure for the benefit of a participated task. Hence, two economic classic tax-based incentive policies: Pivotal Mechanism and Externality Mechanism are applied, to stimulate the participation of tasks. We make simulations in different scenarios including node degree and different characteristics of tasks. The simulations results show that our resource scaling-out mechanism can achieve a better performance close to social optimality.

Existing rateless codes have a very low intermediate symbol recovery rate. Therefore, a new analysis method named iterative and small degree first (I‐SDF) is presented for the design of optimised partial recovery Luby transform codes (PR‐LTC) in this study. On the basis of I‐SDF, the required number of encoded symbols with degree d in each decoding step is calculated by an iterative optimisation algorithm. Under the proposed design, R ( R < k ) input symbols can be recovered from as few encoded symbols as possible in PR‐LTC with message length k . Furthermore, multiple PR‐LTC (M‐PR‐LTC) is proposed to recover several partial recovery point (PRPs) efficiently. The analysis process is divided into multiple stages, and the required number of encoded symbols with degree d in each decoding step is calculated by a cross‐stage iterative optimisation algorithm. In addition, the interaction of each stage is adjusted by introducing a weight for each PRP. The PR‐LTC and M‐PR‐LTC are evaluated and compared with the existing schemes. The simulation results demonstrate that PR‐LTC and M‐PR‐LTC outperform other existing schemes in terms of average overhead, average degree of encoded symbols, memory usage, bit error rate and energy consumption.

Emerging overlay technologies have enabled to distribute content efficiently over the Internet that in some sense improves the user quality of experience. However, due to inconsistent or even conflicting objectives from the perspectives of multiple co-existing overlay networks and traffic engineering (TE), the interaction among them impacts the performance of each other and results in sub- optimum, which also has not yet been investigated in detail. In this paper, we model this interaction as an n+1-person non-cooperative game, prove the existence of Nash equilibrium point (NEP) and propose an algorithm to compute NEP. In order to overcome the inefficiency of NEP, we define a non-transferable utility (NTU) game based on Shapley NTU game theory, in which overlays and TE share cost efficiently and fairly without side payment, and we propose an algorithm to calculate the Shapley NTU value (SNTUV).

Overlay networks have been widely deployed upon the Internet to provide improved network services. However, the interaction between overlay and traffic engineering (TE) as well as among co-existing overlays may occur. In this paper, we adopt game theoretic approaches to analyze this hybrid interaction. Firstly, we model a situation of the hybrid interaction as an n+1-player non-cooperative game, where overlays and TE are of equal status, and prove the existence of Nash equilibrium (NE). Secondly, we model another situation of the hybrid interaction as a 1-leadern-follower Stackelberg-Nash game, where TE is the leader and coexisting overlays are followers, and prove that the cost at Stackelberg-Nash equilibrium (SNE) is at least as good as that at NE for TE. Thirdly, we propose a cooperative coalition mechanism based on Shapley value to overcome the inherent inefficiency of NE and SNE, where players can improve their performance and form stable coalitions.

In complex Internet, different overlay flows are likely to share and compete the same congestible resources. We present a game-theoretic study of the selfish strategic collaboration of multiple overlays when they are allowed to use multipath transfer, which is referred as the multipath selection game. Then we consider the equilibrium in this multipath selection game model where selfish players distribute their overlay traffic. Maximization of the utility functions for each overlay is the criterion of optimality. We adopt the objective of throughput maximization to capture the most typical overlay behaviors, and use the usual TCP as the basis of our analysis. We show analytically the existence and uniqueness of Nash equilibria in these games. Furthermore, we find that the loss of efficiency of Nash equilibria can be arbitrarily large if overlays do not have resource limitations. Our simulations confirm effectiveness and TCP-friendliness of multipath transfer for a range of path number and in the presence of multiple overlay traffic.

As massive data is stored in cloud datacenters, it is necessary to effectively locate interest data in such a distributed environment. However, since it is difficult to create a visual vocabulary due to the lack of global information, most existing systems of Content Based Image Retrieval (CBIR) only focus on global image features. In this paper, we propose a novel image retrieval framework, which efficiently incorporates the bag-of-visual-word model into Distributed Hash Tables (DHTs). Its key idea is to establish visual words for local image features by exploiting the merit of Locality Sensitive Hashing (LSH), so that similar image patches are most likely gathered into the same nodes without the knowledge of any global information. Extensive experimental results demonstrate that our approach yields high accuracy at very low cost, while keeping the load balanced.

In this study, the design of improved Luby transform codes with decreasing ripple size (LTC‐DRS) with feedback is presented. Under the proposed design, a new degree distribution algorithm named generalised degree distribution algorithm (GDDA) is proposed, which can achieve arbitrary ripple size revolution accurately. On the basis of GDDA, an accurate ripple size revolution based on binomial fitting is proposed, which can keep the ripple size to a suitable value throughout the decoding process. Furthermore, the authors introduce the feedback and propose a shifted ripple size revolution to diversify the degree values. The improved LTC‐DRS with feedback is evaluated and compared with the existing schemes. The simulation results demonstrate that it outperforms other existing schemes in terms of average overhead, average degree of encoded symbols, memory usage and energy consumption.

IP multimedia subsystem (IMS) is over IP network architecture, but mobile IP cannot directly support session mobility controlled by session initiation protocol-based signaling. The long signaling delay for session reestablishment in application layer always results in session interruptions during the handoff. Therefore, handoff poses a challenge for quality of service (QoS) maintenance in IMS that targets to offer real-time multimedia applications over wireless mobile networks. The existing approaches to solve this problem depend on the advance resource reservation and the optimization of handoff control. Unfortunately, big cost of the advance resource reservation in neighboring domains is a major problem that leads to a serious signaling load and a waste of wireless bandwidth. To solve this issue, we present an enhanced IMS handoff mechanism (EHM) based on user mobility prediction to save network resources by avoiding multiple useless advance reservations. In addition, to support the heterogeneous access networks in IMS domain, EHM evolves a network selective scheme to utilize the network resources more efficiently. The architecture of EHM and the advance QoS negotiation signaling are also presented. We model the cost, the handoff delay and the session blocking probability for EHM and the previous work. Analytical and simulation results show that EHM can enhance the handoff performance, such as reducing resource reservation cost greatly, decreasing session reestablishment delay and making good use of multiple access network resources.

Deploying a distributed application on the nodes of a network has undoubtedly been a daunting task, which encompasses the distribution as well as the configuration of its components. Deployment and configuration concerns the placement of software components onto the nodes of a target environment, their installation, configuration, and instantiation, as well as the distribution and configuration tasks during the service usage phase. However, they are not fully addressed by the current CORBA component model (CCM). This paper elaborates on the platform architecture for deployment support and proposes the necessary extensions to current CCM.