A Multi-hop Control Network (MCN) consists of a plant where the communication between sensor, actuator and computational unit is supported by a wireless multi-hop communication network, and data flow is performed using scheduling and routing of sensing and actuation data. We address the problem of characterizing controllability and observability of a MCN, by means of necessary and sufficient conditions on the plant dynamics and on the communication scheduling and routing. We provide a methodology to design scheduling and routing, in order to satisfy controllability and observability of a MCN for any fault occurrence in a given set of configurations of failures.
However, what is needed for modeling and analyzing control protocols on multi hop control networks is an integrated framework for analysing co-designing network topology, scheduling, routing, transmission errors and control. To the best of our knowledge, the only formal model of multi-hop wireless sensor and actuator networks is reported in @cite_9 . In this paper, a simulation environment that facilitates simulation of computer nodes and communication networks interacting with the continuous-time dynamics of the real world is presented. The main difference between the work presented in @cite_9 and this work is that here we provide results on a formal mathematical model that takes into account plant dynamics and scheduling-routing dynamics.
@cite_9
2013180246 2114600896 2120997348 2003012549
In multi-hop ad hoc networks, stations may pump more traffic into the networks than can be supported, resulting in high packet-loss rate, re-routing instability and unfairness problems. This paper shows that controlling the offered load at the sources can eliminate these problems. To verify the simulation results, we set up a real 6-node multi-hop network. The experimental measurements confirm the existence of the optimal offered load. In addition, we provide an analysis to estimate the optimal offered load that maximizes the throughput of a multi-hop traffic flow. We believe this is a first paper in the literature to provide a quantitative analysis (as opposed to simulation) for the impact of hidden nodes and signal capture on sustainable throughput. The analysis is based on the observation that a large-scale 802.11 network with hidden nodes is a network in which the carrier-sensing capability breaks down partially. Its performance is therefore somewhere between that of a carrier-sensing network and that of an Aloha network. Indeed, our analytical closed-form solution has the appearance of the throughput equation of the Aloha network. Our approach allows one to identify whether the performance of an 802.11 network is hidden-node limited or spatial-reuse limited. Topology Control (TC) is a well-studied technique used in wireless ad hoc networks to find energy-efficient and or low-interference subgraphs of the maxpower communication graph. However, existing work has the following limitations: (1) the energy model adopted is quite unrealistic - only transmit power is often considered and homogeneous decay of the radio signal with distance is assumed; (2) the interference measure does not account for multi-hop communications. In this paper, we show the dramatic effect of the underlying energy and interference model on TC. In particular, we demonstrate that by using more realistic energy models and considering the effects of multi-hop interference, radically different conclusions about TC can be drawn; namely that (1) energy efficient TC is essentially meaningless, since every link turns out to be "efficient", and that (2) topologies identified as "interference-optimal" in the current literature can be extremely bad from the viewpoint of multi-hop interference. Given these observations, we propose a new measure of link interference, extend it to deal with multi-hop interference, and design a corresponding optimal communication subgraph, called ATASP. We prove that, in the worst case, ATASP coincides with the maxpower communication graph, showing that in some unfortunate situations also performing multi-hop interference-based TC is pointless. However, the simulation results with random node deployments presented in this paper show that, on the average, ATASP is a sparse subgraph of the maxpower communication graph, and multi-hop interference-based TC is indeed possible. Since computing ATASP requires global knowledge, we experiment through simulation with known localized algorithms for energy-efficient TC and show that they perform well (on the average) with respect to multi-hop interference. Remote control over wireless multi-hop networks is considered. Time-varying delays for the transmission of sensor and control data over the wireless network are caused by a randomized multi-hop routing protocol. The characterstics of the routing protocol together with lower-layer network mechanisms give rise to a delay process with high variance and stepwise changing mean. A new predictive control scheme with a delay estimator is proposed in the paper. The estimator is based on a Kalman filter with a change detection algorithm. It is able to track the delay mean changes but efficiently attenuate the high frequency jitter. The control scheme is analyzed and its implementation detailed. Network data from an experimental setup are used to illustrate the efficiency of the approach. Each node in a wireless multi-hop network can adjust the power level at which it transmits and thus change the topology of the network to save energy by choosing the neighbors with which it directly communicates. Many previous algorithms for distributed topology control have assumed an ability at each node to deduce some location-based information such as the direction and the distance of its neighbor nodes with respect to itself. Such a deduction of location-based information, however, cannot be relied upon in real environments where the path loss exponents vary greatly leading to significant errors in distance estimates. Also, multipath effects may result in different signal paths with different loss characteristics, and none of these paths may be line-of-sight, making it difficult to estimate the direction of a neighboring node. In this paper, we present Step Topology Control (STC), a simple distributed topology control algorithm which reduces energy consumption while preserving the connectivity of a heterogeneous sensor network without use of any location-based information. The STC algorithm avoids the use of GPS devices and also makes no assumptions about the distance and direction between neighboring nodes. We show that the STC algorithm achieves the same or better order of communication and computational complexity when compared to other known algorithms that also preserve connectivity without the use of location-based information. We also present a detailed simulation-based comparative analysis of the energy savings and interference reduction achieved by the algorithms. The results show that, in spite of not incurring a higher communication or computational complexity, the STC algorithm performs better than other algorithms in uniform wireless environments and especially better when path loss characteristics are non-uniform.