CONTENT CACHING AND SCHEDULING IN WIRELESS NETWORKS WITH ELASTIC AND INELASTIC TRAFFIC

There is a huge growth in the wireless networks in current days. With this growth, accessing the content through wireless networks needs placing the content at the base stations and scheduling them. Users who are in the network are divided into groups based on the channel conditions, their requests are placed in the front end of the logical queue. All these requests are elastic and inelastic. These requests are placed in the queues which are known as requests queues and the deficit queues contains the deficits which are had in the in elastic services. The data which are stored in the cache are of limited size and they will be getting refreshed frequently to constant time intervals. This paper considering the two different models which will be concentrating on inelastic requests for streaming stored content and real-time streaming of events.  In this paper some of the suggestions are made which are used to design the optimal policies which are used to stabilize the request queues and to reduce the deficit to zer

Scheduling Cached-Content in Wireless Networks With Elastic and Inelastic Traffic

With the exponential growth of wireless content access, the need for content placement and scheduling at wireless base stations increased rapidly. We study a system under which users are divided into clusters based on their channel conditions, and their requests are represented by different queues at logical front ends. Requests might be elastic (implying no hard delay constraint) or inelastic (requiring that a delay target be met). Correspondingly, we have request queues that indicate the number of elastic requests, and deficit queues that indicate the deficit in inelastic service. Caches are of finite size and can be refreshed periodically from a media vault. We consider two cost models that correspond to inelastic requests for streaming stored content and real-time streaming of events, respectively. We design provably optimal policies that stabilize the request queues (hence ensuring finite delays) and reduce average deficit to zero [hence ensuring that the quality-of-service (QoS) target is met] at small cost. We illustrate our approach through simulations

Achieving Quality of Service Guarantees for Delay Sensitive Applications in Wireless Networks

In the past few years, we have witnessed the continuous growth in popularity of delay-sensitive applications. Applications like live video streaming, multimedia conferencing, VoIP and online gaming account for a major part of Internet traffic these days. It is also predicted that this trend will continue in the coming years. This emphasizes the significance of developing efficient scheduling algorithms in communication networks with guaranteed low delay performance. In our work, we try to address the delay issue in some major instances of wireless communication networks. First, we study a wireless content distribution network (CDN), in which the requests for the content may have service deadlines. Our wireless CDN consists of a media vault that hosts all the content in the system and a number of local servers (base stations), each having a cache for temporarily storing a subset of the content. There are two major questions associated with this framework: (i) content caching: which content should be loaded in each cache? and (ii) wireless network scheduling: how to appropriately schedule the transmissions from wireless servers? Using ideas from queuing theory, we develop provably optimal algorithms to jointly solve the caching and scheduling problems. Next, we focus on wireless relay networks. It is well accepted that network coding can enhance the performance of these networks by exploiting the broadcast nature of the wireless medium. This improvement is usually evaluated in terms of the number of required transmissions for delivering flow packets to their destinations. In this work, we study the effect of delay on the performance of network coding by characterizing a trade-off between latency and the performance gain achieved by employing network coding. More specifically, we associate a holding cost for delaying packets before delivery and a transmission cost for each broadcast transmission made by the relay node. Using a Markov decision process (MDP) argument, we prove a simple threshold-based policy is optimal in the sense of minimum long-run average cost. Finally, we analyze delay-sensitive applications in wireless peer-to-peer (P2P) networks. We consider a hybrid network which consists of (i) an expensive base station-to-peer (B2P) network with unicast transmissions, and (ii) a free broadcast P2P network. In such a framework, we study two popular applications: (a) a content distribution application with service deadlines, and (b) a multimedia live streaming application. In both problems, we utilize random linear network coding over finite fields to simplify the coordination of the transmissions. For these applications, we provide efficient algorithms to schedule the transmissions such that some quality of service (QoS) requirements are satisfied with the minimum cost of B2P usage. The algorithms are proven to be throughput optimal for sufficiently large field sizes and perform reasonably well for finite fields

The Role of Caching in Future Communication Systems and Networks

This paper has the following ambitious goal: to convince the reader that content caching is an exciting research topic for the future communication systems and networks. Caching has been studied for more than 40 years, and has recently received increased attention from industry and academia. Novel caching techniques promise to push the network performance to unprecedented limits, but also pose significant technical challenges. This tutorial provides a brief overview of existing caching solutions, discusses seminal papers that open new directions in caching, and presents the contributions of this special issue. We analyze the challenges that caching needs to address today, also considering an industry perspective, and identify bottleneck issues that must be resolved to unleash the full potential of this promising technique

Optimizing Resource Allocation with Energy Efficiency and Backhaul Challenges

To meet the requirements of future wireless mobile communication which aims to increase the data rates, coverage and reliability while reducing energy consumption and latency, and also deal with the explosive mobile traffic growth which imposes high demands on backhaul for massive content delivery, developing green communication and reducing the backhaul requirements have become two significant trends. One of the promising techniques to provide green communication is wireless power transfer (WPT) which facilitates energy-efficient architectures, e.g. simultaneous wireless information and power transfer (SWIPT). Edge caching, on the other side, brings content closer to the users by storing popular content in caches installed at the network edge to reduce peak-time traffic, backhaul cost and latency. In this thesis, we focus on the resource allocation technology for emerging network architectures, i.e. the SWIPT-enabled multiple-antenna systems and cache-enabled cellular systems, to tackle the challenges of limited resources such as insufficient energy supply and backhaul capacity. We start with the joint design of beamforming and power transfer ratios for SWIPT in MISO broadcast channels and MIMO relay systems, respectively, aiming for maximizing the energy efficiency subject to both the Quality of Service (QoS) constraints and energy harvesting constraints. Then move to the content placement optimization for cache-enabled heterogeneous small cell networks so as to minimize the backhaul requirements. In particular, we enable multicast content delivery and cooperative content sharing utilizing maximum distance separable (MDS) codes to provide further caching gains. Both analysis and simulation results are provided throughout the thesis to demonstrate the benefits of the proposed algorithms over the state-of-the-art methods

Cache-Assisted Hybrid Satellite-Terrestrial Backhauling for 5G Cellular Networks

Fast growth of Internet content and availability of electronic devices such as smart phones and laptops has created an explosive content demand. As one of the 5G technology enablers, caching is a promising technique to off-load the network backhaul and reduce the content delivery delay. Satellite communications provides immense area coverage and high data rate, hence, it can be used for large-scale content placement in the caches. In this work, we propose using hybrid mono/multi-beam satellite-terrestrial backhaul network for off-line edge caching of cellular base stations in order to reduce the traffic of terrestrial network. The off-line caching approach is comprised of content placement and content delivery phases. The content placement phase is performed based on local and global content popularities assuming that the content popularity follows Zipf-like distribution. In addition, we propose an approach to generate local content popularities based on a reference Zipf-like distribution to keep the correlation of content popularity. Simulation results show that the hybrid satellite-terrestrial architecture considerably reduces the content placement time while sustaining the cache hit ratio quite close to the upper-bound compared to the satellite-only method