Flexible Resource Management in Wireless Networks
- Author(s): Singh, Shailendra
- Advisor(s): Krishnamurthy, Srikanth V
- et al.
Surging data demand driven by the proliferation of smartphones is revolutionizing the wire- less scene. By 2020, the number of smartphone subscribers will grow to 9 billion and the demand in mobile data traffic will grow 10 folds. Capacity (bandwidth) and Latency are the key contributing factors to a positive user experience. For example, streaming a video from Netflix or Youtube is bandwidth limited while loading or browsing the Youtube or Net- flix website is latency limited. One can argue that by using more spectrum(wider wireless channels) can solve the capacity problem however according to Federal Communications Commission(FCC) we are already facing a spectrum deficit. Newer network technologies like 4G and LTE have improved the network performance(both capacity and latency) but 60world’s mobile subscribers will still be using the slower 3G or 2G connections for at least a decade. Another challenge that mobile devices are posing is that the networks previously dominated by the static users (or static channel conditions) with devices like laptops are increasingly becoming more heterogeneous( mix of static and mobile users with varying channel conditions).
In this dissertation, I address the issue of managing wireless resources to support various multimedia applications, in wireless networks with a high degree of user mobility. Driven by necessity for flexible wireless resource management, I design, build and eval- uate three wireless resource management schemes. First, I present JPRA, a joint power and rate adaptation scheme which adaptively distributes uneven power levels of OFDMA sub-carriers to cope with frequency selectivity in fading. Thus, improves the total network capacity. Second, I present TRINITY, a practical transmitter cooperation scheme to handle heterogeneous user profiles in wireless networks. Sophisticated MIMO-based transmission strategies, based on transmitter cooperation, have emerged recently. However, different types of users profiles (e.g., static vs mobile, stable vs dynamic channels) that make up todays enterprises, require different MIMO transmission strategies(CMSA, Network MIMO and DAS). With the wrong strategy, a user could even see a degradation in performance. TRINITY can simultaneously cater to a heterogeneous mix of users, by intelligently com- bining a plurality of MIMO transmission strategies wherein the transmitters at different nodes can cooperate to deliver significant performance gains.
Next, I present FluidNet, a scalable, light-weight framework for realizing the full potential of Cloud-based radio access networks(C-RAN). Cloud-based radio access networks (C-RAN) have been proposed as a cost-efficient way of deploying small cells. In this work, we argue that the intelligent configuration of the front-haul network between the baseband processing units(BBUs) and remote radio heads, is essential in delivering the performance and energy benefits to the RAN and the BBU pool, respectively. FluidNet deploys a logically re-configurable front-haul to apply appropriate transmission strategies in different parts of the network and hence cater effectively to both heterogeneous user profiles and dynamic traffic load patterns.
Finally, I present FlexiWeb, a network aware compaction scheme for accelerat- ing mobile web transfers. Latency is often cited as the main reason for poor mobile web performance and to reduce the page load times, middleboxes that compress page content are commonly used today. Unfortunately, this can hurt performance in many cases. Our measurements reveal that the middlebox should be used only when network conditions are bad; otherwise, most objects in the web page should be directly fetched from the source web server. Based on this observation we build FlexiWeb, a framework that supports network- aware middlebox usage and performs dynamic network-aware compression to provide further performance gains.