Resource Allocation in Communications and Computing

Yi Su, Fangwen Fu, Shuo Guo
2013 Journal of Electrical and Computer Engineering  
Communication networks and computing systems have demonstrated their importance in the past few decades as a fundamental driver of economic growth. Over the years, they have not only expanded in their sizes, such as geographical area and number of terminals, but also in the variety of services, users, and deployment environments. The purpose of resource allocation in such environments is to intelligently assign the limited available resources among terminals/clients in an efficient way to
more » ... y end users' service requirements. With the dramatic developments and fast evolution of communication networks and computing systems, resource allocation continues to be the fundamental challenge, because better quality of service is required with the increasing demand for bandwidth-hungry and/or computationintensive services. In particular, it has to cope with various new emerging system architectures, such as cognitive networks, mesh networks, multihop networks, peer-to-peer networks, multistandard networks, cloud computing systems, and data centers, distributed intelligence in a multitude of devices operating autonomously enables shifting traditional centralized allocation mechanisms into fully distributed solutions. In recent years, many tools including optimization theory, control theory, game theory, and auction theory have been employed to model and solve a variety of practical resource allocation problems. Therefore, resource allocation in communication networks and computing systems is a pressing research topic that has huge applications. It is imperative to develop advanced resource allocation techniques for ensuring the optimal performance of these systems and networks. The goal of this special issue is to bring together the most updated research contributions in this area. Indeed, we see a wide range of new analytical techniques and novel application scenarios emerging as evidenced in the papers presented here. The nine accepted papers are relevant to resource allocations optimizations in orthogonal frequency division multiplexing (OFDM-) based communication systems, cognitive radio, satellite communications, grid computing, and network virtualization. J. Y. Baudais et al. in "Robustness maximization of parallel multichannel systems," study bit-loading solutions of both robustness optimization problems over independent parallel channels. Their investigation is based on analytical approach, using generalized Lagrangian relaxation tool, and on greedytype algorithm approach. The asymptotic convergence of both robustness optimizations is proved for both analytical and algorithmic approaches. They also link the SNR-gap maximization problem to the conventional power minimization problem and prove that the duality does not hold in all cases. In nonasymptotic regime, they show that the resource allocation policies can be interchanged depending on the robustness measure and the operating point of the communication system. They propose a low-complexity resource allocation algorithm based on the analytical approach, which leads to a good tradeoff between performance and complexity. C. Guéguen and S. Baey, in "Comparison study of resource allocation strategies for OFDM multimedia networks," present and compare the main OFDM scheduling techniques used for multimedia services in multiuser OFDM wireless networks. They study the influence of bandwidth granularity on the resource allocation strategies performances. They show that
doi:10.1155/2013/328395 fatcat:7rdkzogcwne3hh2hfwui6sj5zy