Intelligent fluid infrastructure for embedded networks

Abstract

Computer networks have historically considered support for mobile devices as an extra overhead to be borne by the system. Recently however, researchers have proposed methods by which the network can take advantage of mobile components. We exploit mobility to develop a fluid infrastructure: mobile components are deliberately built into the system infrastructure for enabling specific functionality that is very hard to achieve using other methods. Built-in intelligence helps our system adapt to run time dynamics when pursuing pre-defined performance objectives. Our approach yields significant advantages for energy constrained systems, sparsely deployed networks, delay tolerant networks, and in security sensitive situations. We first show why our approach is advantageous in terms of network lifetime and data fidelity. Second, we present adaptive algorithms that are used to control mobility. Third, we design the communication protocol supporting a fluid infrastructure and long sleep durations on energy-constrained devices. Our algorithms are not based on abstract radio range models or idealized unobstructed environments but founded on real world behavior of wireless devices. We implement a prototype system in which infrastructure components move autonomously to carry out important networking tasks. The prototype is used to validate and evaluate our suggested mobility control methods.

A Survey on Localization for Mobile Wireless Sensor Networks

“…By using mobile base stations, this problem is eliminated, and the lifetime of the network is extended [19]. Mobility also enables greater channel capacity and maintains data integrity by creating multiple communication pathways, and reducing the number of hops messages must travel before reaching their destination [20].…”

A framework for Resource-Aware Data Accumulation in sparse wireless sensor networks

“…However, as the proposed approach is devised for opportunistic networks, it cannot be used without being redesigned in the scenario considered in this paper. Many subsequent papers specifically focused on WSNs with MDCs, including [4,[9][10][11][12]. However, they assume that the operating parameters are chosen prior to deployment, and do not change with time.…”

Joint mobility and routing for lifetime elongation in wireless sensor networks

“…It would be interesting to have a theoretical analysis on this hybrid approach. Our proposal differs from [15], [16], [28] in that we do not apply the mobile relay approach; as a result, the moving speed, which is crucial in their cases due to its impact on latency, is not essential any more to our solution. Finally, it is also important to note that the mobility of network nodes can facilitate sensor deployment [38], reduce sensing uncertainty [39], and act as a network control primitive to improve communication performance in ad hoc networks [40].…”

“…The robot provides a power supply for the node and also carries communication facilities that enable the base station to communicate with devices outside the considered sensor network. A detailed design of a mobile base station is out of the scope of this paper; a brief introduction can be found in [13], [28]. It is important to note that, in order to achieve a balanced load distribution, the mobility period (i.e., the time to complete one round along a trajectory) should divide the network lifetime.…”

“…Also, their proposals leverage only on uncontrollable (although predictable for [16]) mobility of the base station. The controllable mobility was recently investigated in [28]. This proposal is a compromise between the mobile relay approach and ours: the base station still relays data with its movements, but a node that does not lie in the vicinity of the mobility trajectory transmits data through a multi-hop routing when the base station moves to the closest point to the node.…”