Energy Efficient and Guaranteed Packet Delivery in Mobile Ad Hoc Networks

For Ad-hoc network routing protocols, high delivery ratio with low energy consumption is one of design challenges. This paper identifies the limitations of ad hoc routing scheme, in terms of guaranteed delivery with low energy consumption. Accordingly, this paper describe a scheme, in which data is forwarded along a pre-established lone path to save energy, and a high delivery ratio is completed by path repair whenever a break is detected. This paper propose a humble, quick, local path repairing method, whereby a malicious node can be tracked by low energy. This paper implement encoding and compression technique scheme and compare its performance with those of pure lone path without repair and multi-path routing schemes

MIGRATE: mobile device virtualisation through state transfer

Delegation of processing tasks to the network has moved from cloud-based schemes to edge computing solutions where nearby servers process requests in a timely manner. Virtualisation technologies have recently given data cloud and network providers the required flexibility to offer such on-demand resources. However, the maintenance of close computing resources presents a challenge when the served devices are on the move. In this case, if processing continuity is desired, a transference of processing resources and task state should be committed to maintain the service to end devices. The solution here presented, MIGRATE, proposes the concept of virtual mobile devices (vMDs) implemented as Virtual Functions (VxF) and acting as virtual representatives of physical processing devices. vMDs are instantiated at the edge of the access network, following a Multi-Access Edge Computing (MEC) approach, and move across different virtualisation domains. MIGRATE provides seamless and efficient transference of these software entities to follow the real location of mobile devices and continue supporting their physical counterparts. Software Defined Networks and Management and Operation functions are exploited to “migrate” vMDs to new virtualisation domains by forwarding data flows to the former domain until the new one is prepared, while a distributed data base avoids the transference of data. The solution has been deployed in a reference vehicular scenario at the Institute of Telecommunications Aveiro premises within the 5GINFIRE European project. In particular, the system has been evaluated under different virtualisation domains to study the operation of the migration approach in a vehicular monitoring scenario. The results validate the system from the application viewpoint with a Web monitoring tool, and the migration of the digital twin provided as VxF is analysed attending to the modification of data flows, indicating a seamless transition between virtualisation domains in a timely manner.publishe

Flooding Data in a Cell: Is Cellular Multicast Better than Device-to-Device Communications?

International audienceA natural method to disseminate popular data on cellular networks is to use multicast. Despite having clear advantages over unicast, multicast does not offer any kind of reliability and could result costly in terms of cellular resources in the case at least one of the destinations is at the edge of the cell (i.e., with poor radio conditions). In this paper, we show that, when content dissemination tolerates some delay, providing device-to-device communications over an orthogonal channel increases the efficiency of multicast, concurring also to offload part of the traffic from the infrastructure. Our evaluation simulates an LTE macro-cell with mobile receivers and reveals that the joint utilization of device-to-device communications and multicasting brings significant resource savings while increasing the cellular throughput

Introducing the new paradigm of Social Dispersed Computing: Applications, Technologies and Challenges

[EN] If last decade viewed computational services as a utility then surely this decade has transformed computation into a commodity. Computation is now progressively integrated into the physical networks in a seamless way that enables cyber-physical systems (CPS) and the Internet of Things (IoT) meet their latency requirements. Similar to the concept of ¿platform as a service¿ or ¿software as a service¿, both cloudlets and fog computing have found their own use cases. Edge devices (that we call end or user devices for disambiguation) play the role of personal computers, dedicated to a user and to a set of correlated applications. In this new scenario, the boundaries between the network node, the sensor, and the actuator are blurring, driven primarily by the computation power of IoT nodes like single board computers and the smartphones. The bigger data generated in this type of networks needs clever, scalable, and possibly decentralized computing solutions that can scale independently as required. Any node can be seen as part of a graph, with the capacity to serve as a computing or network router node, or both. Complex applications can possibly be distributed over this graph or network of nodes to improve the overall performance like the amount of data processed over time. In this paper, we identify this new computing paradigm that we call Social Dispersed Computing, analyzing key themes in it that includes a new outlook on its relation to agent based applications. We architect this new paradigm by providing supportive application examples that include next generation electrical energy distribution networks, next generation mobility services for transportation, and applications for distributed analysis and identification of non-recurring traffic congestion in cities. The paper analyzes the existing computing paradigms (e.g., cloud, fog, edge, mobile edge, social, etc.), solving the ambiguity of their definitions; and analyzes and discusses the relevant foundational software technologies, the remaining challenges, and research opportunities.Garcia Valls, MS.; Dubey, A.; Botti, V. (2018). Introducing the new paradigm of Social Dispersed Computing: Applications, Technologies and Challenges. Journal of Systems Architecture. 91:83-102. https://doi.org/10.1016/j.sysarc.2018.05.007S831029