Instantaneous multi-sensor task allocation in static and dynamic environments

A sensor network often consists of a large number of sensing devices of different types. Upon deployment in the field, these sensing devices form an ad hoc network using wireless links or cables to communicate with each other. Sensor networks are increasingly used to support emergency responders in the field usually requiring many sensing tasks to be supported at the same time. By a sensing task we mean any job that requires some amount of sensing resources to be accomplished such as localizing persons in need of help or detecting an event. Tasks might share the usage of a sensor, but more often compete to exclusively control it because of the limited number of sensors and overlapping needs with other tasks. Sensors are in fact scarce and in high demand. In such cases, it might not be possible to satisfy the requirements of all tasks using available sensors. Therefore, the fundamental question to answer is: “Which sensor should be allocated to which task?", which summarizes the Multi-Sensor Task Allocation (MSTA) problem. We focus on a particular MSTA instance where the environment does not provide enough information to plan for future allocations constraining us to perform instantaneous allocation. We look at this problem in both static setting, where all task requests from emergency responders arrive at once, and dynamic setting, where tasks arrive and depart over time. We provide novel solutions based on centralized and distributed approaches. We evaluate their performance using mainly simulations on randomly generated problem instances; moreover, for the dynamic setting, we consider also feasibility of deploying part of the distributed allocation system on user mobile devices. Our solutions scale well with different number of task requests and manage to improve the utility of the network, prioritizing the most important tasks.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Cross-layer design of multi-hop wireless networks

MULTI -hop wireless networks are usually defined as a collection of nodes equipped with radio transmitters, which not only have the capability to communicate each other in a multi-hop fashion, but also to route each others’ data packets. The distributed nature of such networks makes them suitable for a variety of applications where there are no assumed reliable central entities, or controllers, and may significantly improve the scalability issues of conventional single-hop wireless networks. This Ph.D. dissertation mainly investigates two aspects of the research issues related to the efficient multi-hop wireless networks design, namely: (a) network protocols and (b) network management, both in cross-layer design paradigms to ensure the notion of service quality, such as quality of service (QoS) in wireless mesh networks (WMNs) for backhaul applications and quality of information (QoI) in wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of this Ph.D. dissertation, different network settings are used as illustrative examples, however the proposed algorithms, methodologies, protocols, and models are not restricted in the considered networks, but rather have wide applicability. First, this dissertation proposes a cross-layer design framework integrating a distributed proportional-fair scheduler and a QoS routing algorithm, while using WMNs as an illustrative example. The proposed approach has significant performance gain compared with other network protocols. Second, this dissertation proposes a generic admission control methodology for any packet network, wired and wireless, by modeling the network as a black box, and using a generic mathematical 0. Abstract 3 function and Taylor expansion to capture the admission impact. Third, this dissertation further enhances the previous designs by proposing a negotiation process, to bridge the applications’ service quality demands and the resource management, while using WSNs as an illustrative example. This approach allows the negotiation among different service classes and WSN resource allocations to reach the optimal operational status. Finally, the guarantees of the service quality are extended to the environment of multiple, disconnected, mobile subnetworks, where the question of how to maintain communications using dynamically controlled, unmanned data ferries is investigated