Green, Trust and Computation Offloading Perspectives for Optimizing Network Management and Mobile Services

Today's advances of mobile communication technologies along with hardware and software improvement of mobile devices has pushed to the Internet of Things (IoT) era, with the ultimate aim of providing advanced connectivity of physical entities, systems and services to make our environment smarter and more manageable. With the development of 5G communication network, the pervasive use of diverse objects is expected to speed up and the network backbone has been enriched accordingly with more and more resources in terms of bandwidth, processing power and memory to be capable to satisfy the influx of today and emerging services.
In such a context, we tackle three research challenges, namely green management of network resources, computation offloading for mobile cloud computing and trust management for mobile ad hoc networks. With regard to green network management perspective, we focus mainly on dynamic switching off extra nodes and links during low traffic periods. Our main objective is hence to determine the appropriate residual topology composed of network routers and links which allows to respect the trade-off between energy conservation and network performance. In this regard, we propose a distributed green network management architecture along with several QoS-aware sleep-scheduling approaches with or without information on network traffic. Moreover, a joint sleep-scheduling and adaptive link rate green mechanism is proposed to adapt the capacity of residual topology to match the real network usage.
With regard to mobile computation offloading perspective, our main goal is to make an appropriate offloading decision which improves the energy and time of application execution. In this regard, we emphasize on reducing the time and energy of partitioning algorithm, self-adapting the offloading decision according to underlying wireless environment, mobility-awareness of offloading decision and computation offloading in multi-site context.
Finally, in the trust management perspective, we mainly focus on proposing approaches to detect double-face and bad mouthing conducts in conflicting multi-attack MANET environments. In a multi-attack environment with both double-face and bad mouthing conduct, nodes may confuse to consider a very different opinion as an indication for dishonest recommendation or the perception of a victim of a double-face attacker. In addition, we tackle the problem of energy consumption of trust systems and propose a green trust system capable to conserve the energy consumption devoted to trust system, while keeping the capacity to detect simultaneous double-face and bad mouthing attackers.