Current Issue : April - June Volume : 2012 Issue Number : 2 Articles : 6 Articles
This paper deals with radio resource allocation in fourth generation (4G) wireless mobile networks based on Orthogonal\r\nFrequency Division Multiple Access (OFDMA) as an access method. In IEEE 802.16m standard, a contiguous method for\r\nsubchannel construction is adopted in order to reduce OFDMA system complexity. In this context, we propose a new subchannel\r\ngain computation method depending on frequency responses dispersion. This method has a crucial role in the resource\r\nmanagement and optimization. In a single service access, we propose a dynamic resource allocation algorithm at the physical layer\r\naiming to maximize the cell data rate while ensuring fairness among users. In heterogeneous data traffics, we study scheduling in\r\norder to provide delay guaranties to real-time services, maximize throughput of non-real-time services while ensuring fairness to\r\nusers.We compare performances to recent existing algorithms in OFDMA systems showing that proposed schemes provide lower\r\ncomplexity, higher total system capacity, and fairness among users....
A system data sharing protocol of mobile WSN named synchronous dynamic multihop data sharing protocol (S-DMDS) is\r\npresented for automated guided vehicle (AGV) system. It is a cross-layer protocol designed from route layer to MAC layer. By\r\nadopting a concept of system data sharing, it is possible to make each node exchange the data timely with all the other nodes. It\r\nis also a topology-agnostic protocol which has no knowledge of neighbors, routes, or next hops. From the results of the 16-nodes\r\nsimulation, S-DMDS protocol is proved to be efficient exchange data timely between the devices of AGV system in mobile multihop\r\nsituation.Moreover, it also shows that S-DMDS significantly outperforms NST-AODV with investing about 41.6% system sharing\r\ndelay as well as 80% RAM consumption. At last, 5-node experiment indicates that S-DMDS can work well in real environment....
This paper provides an innovative solution, namely, the distributed storage manager that opens a new path for highly interactive\nand personalized services. The distributed storage manager provides an enhancement to the MHP storage management\nfunctionality acting as a value added middleware distributed across the network. The distributed storagemanager system provides\nmultiple protocol support for initializing and downloading both streamed and file-based content and provides optimum control\nmechanisms to organize the storing and retrieval of content that are remained accessible to other multiple heterogeneous devices....
Task assignment in grid computing, where both processing and bandwidth constraints at multiple heterogeneous devices need\r\nto be considered, is a challenging problem. Moreover, targeting the optimization of multiple objectives makes it even more challenging.\r\nThis paper presents a task assignment strategy based on genetic algorithms in whichmultiple and conflicting objectives are\r\nsimultaneously optimized. Specifically, we maximize task execution quality while minimizing energy and bandwidth consumption.\r\nMoreover, in our video processing scenario; we consider transcoding to lower spatial/temporal resolutions to tradeoff between\r\nvideo quality; processing, and bandwidth demands. The task execution quality is then determined by the number of successfully\r\nprocessed streams and the spatial-temporal resolution at which they are processed. The results show that the proposed algorithm\r\noffers a range of Pareto optimal solutions that outperforms all other reference strategies....
The increasing popularity of network-based multimedia applications poses many challenges for content providers to supply\nefficient and scalable services. Peer-to-peer (P2P) systems have been shown to be a promising approach to provide large-scale\nvideo services over the Internet since, by nature, these systems show high scalability and robustness. In this paper, we propose\nand analyze an object management policy approach for video web cache in a P2P context, taking advantage of object�s metadata,\nfor example, video popularity, and object�s encoding techniques, for example, scalable video coding (SVC). We carry out tracedriven\nsimulations so as to evaluate the performance of our approach and compare it against traditional object management\npolicy approaches. In addition, we study as well the impact of churn on our approach and on other object management policies\nthat implement different caching strategies. A YouTube video collection which records over 1.6 million video�s log was used in\nour experimental studies. The experiment results have showed that our proposed approach can improve the performance of the\ncache substantially. Moreover, we have found that neither the simply enlargement of peers� storage capacity nor a zero replicating\nstrategy is effective actions to improve performance of an object management policy....
The emergence of cloud encoding services facilitates many content owners, such as the online video vendors, to transcode their\r\ndigital videos without infrastructure setup. Such service provider charges the customers only based on their resource consumption.\r\nFor both the service provider and customers, lowering the resource consumption while maintaining the quality is valuable and\r\ndesirable. Thus, to choose a cost-effective encoding parameter, configuration is essential and challenging due to the tradeoff\r\nbetween bitrate, encoding speed, and resulting quality. In this paper, we explore the feasibility of an automatic parameter-tuning\r\nframework, based on which the above objective can be achieved.We introduce a simple service model, which combines the bitrate\r\nand encoding speed into a single value: encoding cost. Then, we conduct an empirical study to examine the relationship between\r\nthe encoding cost and various parameter settings. Our experiment is based on the one-pass Constant Rate Factor method in x264,\r\nwhich can achieve relatively stable perceptive quality, and we vary each parameter we choose to observe how the encoding cost\r\nchanges. The experiment results show that the tested parameters can be independently tuned to minimize the encoding cost,\r\nwhich makes the automatic parameter-tuning framework feasible and promising for optimizing the cost on video encoding cloud....
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