Efficient and adaptive congestion control for heterogeneous delay-tolerant networks

Detecting and dealing with congestion in delay-tolerant networks (DTNs) is an important and challenging problem. Current DTN forwarding algorithms typically direct traffic towards more central nodes in order to maximise delivery ratios and minimise delays, but as traffic demands increase these nodes may become saturated and unusable. We pro- pose CafRep, an adaptive congestion aware protocol that detects and reacts to congested nodes and congested parts of the network by using implicit hybrid contact and resources congestion heuristics. CafRep exploits localised relative utility based approach to offload the traffic from more to less congested parts of the network, and to replicate at adaptively lower rate in different parts of the network with non-uniform congestion levels. We extensively evaluate our work against benchmark and competitive protocols across a range of metrics over three real connectivity and GPS traces such as Sassy [44], San Francisco Cabs [45] and Infocom 2006 [33]. We show that CafRep performs well, independent of network connectivity and mobility patterns, and consistently outperforms the state-of-the-art DTN forwarding algorithms in the face of increasing rates of congestion. CafRep maintains higher availability and success ratios while keeping low delays, packet loss rates and delivery cost. We test CafRep in the presence of two application scenarios, with fixed rate traffic and with real world Facebook application traffic demands, showing that regardless of the type of traffic CafRep aims to deliver, it reduces congestion and improves forwarding performance

Efficient data access in mobile cloud computing

This thesis focuses on the development of efficient data transfer mechanism among mobile devices using Mobile cloud computing paradigm. Mobile cloud computing is coupling of mobile computing and cloud computing. In the Mobile cloud computing paradigm, users connect to cloud service providers over the Internet and leverage the cloud resources to perform their processing, storage and communication tasks. In this thesis, the focus is on communication tasks among mobile devices performed using Mobile cloud computing paradigm. Communication or data sharing among mobile devices is often limited by proximity of the devices. This limitation can be removed by employing Mobile cloud computing paradigm wherein each physical mobile device has a corresponding virtual machine in the cloud servers. All the computation and communication tasks can be offloaded to the virtual machines in the cloud retaining only a thin client in the physical device to display results. The exchange of data or communication between mobile devices is done through the corresponding virtual machines in the cloud. In this work, we designed a layered architecture involving mobile devices, access points and cloud server together for efficiency. We also proposed pre-distribution scheme based on this architecture for efficient data sharing among potential users with supporting data access mechanism, update propagation mechanism and cache replacement mechanisms. We also performed complexity analysis for data access using the proposed architecture and scheme. Finally, simulated the proposed architecture and scheme with actual devices and verified the efficiency of the scheme. --Abstract, page iv

Social distributed content caching in federated residential networks

This work addresses the need for content sharing and backup in household equipped with a home gateway that stores, tags and manages the data collected by the home users. Our solution leverages the interaction between remote gateways in a social way, i.e., by exploiting the users' social networking information, so that caching recipients are those gateways whose users are most likely to be interested in accessing the shared content. We formulate this problem as a Budgeted Maximum Coverage (BMC) problem and we numerically compute the optimal content caching solution. We then propose a low-complexity, distributed heuristic algorithm and use simulation in a synthetic social network scenario to show that the final content placement among "friendly" gateways well approximates the optimal solution under different network setting