Peer-to-Peer (P2P) file sharing protocols for Mobile Ad Hoc networks (MANETS) is becoming an important area of research nowadays because of the constantly escalating demands from consumers to go mobile and the need to share contents between users. Current P2P file sharing protocols for MANETs use either aggressive or reactive flooding techniques for their path selection and recovery. Both techniques represent extreme measures to deal with path failures and they either do too much or very little work in response to path failures. In this paper we present a new path selection and recovery mechanism (Reactive with Unicast Probing Messages) that is a balance between the above two techniques in terms of its control overhead and the resulting path quality. By introducing a new unicast messaging mechanism to the reactive flooding technique, a requesting node can probe its set of available paths for their roundtrip times and use the best one for its file transfer. Our new technique is based on unicast messaging which proves to be effective and requires low control overhead as per the results of our simulations.

Grid balancing is an essential requirement for power grid systems. This requirement has traditionally been fulfilled by existing flexibility mechanisms that provide voltage and frequency regulation. However, the recent interests in greening the energy supply by using more renewable energy sources present new grid balancing challenges. Such volatile energy sources introduce generation-side uncertainty and cause the flexibility mechanisms to fall short more often on providing enough balancing capacity. In this paper, we target the problem of balancing surplus energy from renewable sources by selling it in an auction to allow for its quick consumption. Our solution uses cloud datacenters as managed loads by incentivizing inter-datacenter cloud workload migrations through the auction sale of excess energy. It leverages the programmability and energy-demands flexibility of cloud datacenters, and uses incentivized cloud workload migrations to increase the energy consumption of a datacenter in a certain location to consume its excess energy. We propose an integrated auctioning-scheduling mechanism that auctions the surplus energy and schedules its consumption on a cloud datacenter. The auction part incentivizes the inter-datacenter cloud workload migrations, while the scheduling part ensures that migrated workloads do not exceed the destination datacenter capacity. Existing datacenter-based grid balancing approaches have focused on providing downward flexibility and only considered the case of owner-operated datacenters. In contrast, our system focuses on providing upward flexibility to target the increasingly frequent problem of excess energy from renewables, and it uses public cloud datacenters to increase the participation of datacenters in providing demand-side flexibility. Conducted simulation experiments show the effectiveness of our approach in ramping up the energy consumption of a target datacenter to minimize the time needed to consume the excess energy by as much as 75%. Plus, selling excess energy in an auction was shown to salvage 55%-65% of its original cost and provide 10% of cost savings to buyers.

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