Opportunistic network applications are usually assumed to work only with unordered immutable messages, like photos, videos or music files, while applications that depend on ordered or mutable messages, like chat or shared contents editing applications, are ignored. In this chapter, we examine how causal and total ordering can be achieved in an opportunistic network. By leveraging on existing dissemination algorithms, we investigate if causal order can be efficiently achieved in terms of hit rate and latency compared to not using any order. Afterwards, we propose a Commutative Replicated Data Type algorithm based on Logoot that uses the nature of opportunistic networks to its advantage. Finally, we present the results of the experiments for the new algorithm by using an opportunistic network emulator, mobility traces and chat traces.

Summary Opportunistic network applications are usually assumed to work only with unordered immutable messages, like photos, videos, or music files, while applications that depend on ordered or mutable messages, like chat or shared contents editing applications, are ignored. In this paper, we examine how total ordering can be achieved in an opportunistic network. By leveraging on existing dissemination and causal order algorithms, we propose a commutative replicated data type algorithm on the basis of Logoot for achieving total order without using tombstones in opportunistic networks where message delivery is not guaranteed by the routing layer. Our algorithm is designed to use the nature of the opportunistic network to reduce the metadata size compared to the original Logoot, and even to achieve in some cases higher hit rates compared to the dissemination algorithms when no order is enforced. Finally, we present the results of the experiments for the new algorithm by using an opportunistic network emulator, mobility traces, and Wikipedia pages.

Smartphones have shaped the mobile computing community. Unfortunately, their power consumption overreaches the limits of current battery technology. Most solutions for energy efficiency turn towards offloading code from the mobile device into the cloud. Although mobile cloud computing inherits all the Cloud Computing advantages, it does not treat user mobility, the lack of connectivity, or the high cost of mobile network traffic. In this chapter, the authors introduce mobile-to-mobile contextual offloading, a novel collaboration concept for handheld devices that takes advantage of an adaptive contextual search algorithm for scheduling mobile code execution over smartphone communities, based on predicting the availability and mobility of nearby devices. They present the HYCCUPS framework, which implements the contextual offloading model in an on-the-fly opportunistic hybrid computing cloud. The authors emulate HYCCUPS based on real user traces and prove that it maximizes power saving, minimizes overall execution time, and preserves user experience.