Double loop computer networks are widely used in the design and implementation of local area networks and parallel processing architectures. However the embedding problems on double-loop networks have not been well studied due to the complexity of double-loop networks. Since the traditional L-shape, designed to compute the diameter of double-loop networks, is not efficient to solve embedding problems, we propose a novel tessellation approach to partition the geometric plane of double-loop networks into a set of parallelogram shaped tiles, called P-shape. Our proposed tessellation technique, P-shape, is a useful theoretical tool for embedding meshes on double-loop networks, and can be extended to analyze other problems as a bridge between regular graphs and double-loop networks.
Achieving low-power operation in wireless sensor networks with high data load or bursty traffic is challenging. The hidden terminal problem is aggravated with increased amounts of data in which traditional backoff-based contention resolution mechanisms fail or induce high latency and energy costs. We analyze and optimize Strawman, a receiver-initiated contention resolution mechanism that copes with hidden terminals. We propose new techniques to boost the performance of Strawman while keeping the resolution overhead small. We finally validate our improved mechanism via experiments.
This paper describes a methodology for controller and communication scheduling co-design in control systems operating over wirelessHART networks. Data collection and dissemination operations are identified and scheduled to minimize the nominal communication latency. Techniques for improving the reliability of the network when link transmissions are unreliable are discussed, and a Markov-chain model for computing the latency distribution of data collection operations for a given schedule is proposed. The resulting latency models allow to represent the networked control loop as a jump-linear system, whose performance can be analyzed using techniques from stochastic control. We demonstrate how this framework can be used to co-design a networked LQG controller for a five-by-five MIMO control loop.
Real-time data delivery is a critical issue in wirelessHART networks. This paper develops a novel mathematical programming framework for joint routing and link scheduling of deadline-constrained traffic in wirelessHART networks. The general framework explores dynamic network flows on a time-expanded graph model and can provide flexible solutions for a variety of real-time data delivery problems. Data evacuation, an important communication paradigm in wirelessHART networks, is a special case of this general framework. We establish the lower bound on evacuation time for line, multi-line and binary tree networks. Moreover, we design a novel scheduling algorithm for data evacuation in binary tree networks, and prove that this scheduling algorithm can always achieve the lower bound on evacuation time. We evaluate our scheduling algorithm through numerical simulations, and results show that our algorithm can always minimize the evacuation time with the least number of channels.
The traditionally wired automation infrastructure is quickly migrating to more flexible and scalable wireless solutions. To cope with the stringent requirements of process automation in terms of latency and reliability, the network resources must be optimized to ensure timely and reliable communication. This paper considers the joint routing and transmission scheduling problem for reliable real-time communication over lossy networks. Specifically, we impose a strict latency bound for packet delivery from source to destination, and devise optimal transmission scheduling policies that maximize the success probability of delivering the packet within the specified deadline. A solution to this problem allows to characterize the set of achievable latencies and packet reliability for a given network. We offer a complete understanding of the problem when erasure events on links are independent and follow a Bernoulli process. We consider both static and dynamic resource allocation policies, and compare them in numerical examples.
Geographic routing is an attractive localized routing scheme for wireless sensor networks (WSNs) due to its desirable scalability and efficiency. Maintaining neighborhood information for packet forwarding can achieve a high efficiency in geographic routing, but may not be appropriate for WSNs in highly dynamic scenarios where network topology changes frequently due to nodes mobility and availability. We propose a novel online routing scheme, called Energy-efficient Beaconless Geographic Routing (EBGR), which can provide loop-free, fully stateless, energy-efficient sensor-to-sink routing at a low communication overhead without the help of prior neighborhood knowledge. In EBGR, each node first calculates its ideal next-hop relay position on the straight line toward the sink based on the energy-optimal forwarding distance, and each forwarder selects the neighbor closest to its ideal next-hop relay position as the next-hop relay using the Request-To-Send/Clear-To-Send (RTS/CTS) handshaking mechanism. We establish the lower and upper bounds on hop count and the upper bound on energy consumption under EBGR for sensor-to-sink routing, assuming no packet loss and no failures in greedy forwarding. Moreover, we demonstrate that the expected total energy consumption along a route toward the sink under EBGR approaches to the lower bound with the increase of node deployment density. We also extend EBGR to lossy sensor networks to provide energy-efficient routing in the presence of unreliable communication links. Simulation results show that our scheme significantly outperforms existing protocols in wireless sensor networks with highly dynamic network topologies.
Convergecast, in which data from a set of sources is routed toward one data sink, is a critical functionality for wireless networks deployed for industrial monitoring and control. We address the joint link scheduling and channel assignment problem for convergecast in networks operating according to the recent WirelessHART standard. For a linear network with N single-buffer devices, we demonstrate that the minimum time to complete convergecast is 2N - 1 time-slots, and that the minimum number of channels required for this operation is inverted right perpendicularN/2inverted left perpendicular. When the devices are allowed to buffer multiple packets, we prove that the optimal convergecast time remains the same while the number of required channels can be reduced to inverted right perpendicularN - root N-(N-1)/2inverted left perpendicular. For both cases, we present jointly time- and channel-optimal scheduling policies with complexity O(N-2). Numerical results demonstrate that our schemes are also efficient in terms of memory utilization.
The increased industrial interest in wireless sensor networks demands a shift from optimizing protocols for reporting sporadic events, to solutions for high-rate data collection and dissemination. We study time-optimal convergecast under the communication constraints of commodity sensor network platforms. We propose a novel convergecast model in which packet copying between the microcontroller and the radio transceiver is separated from packet transmission, thereby improving channel utilization and system throughput. Based on this model, we establish the tight lower bound on the number of time slots for convergecast in networks with tree routing topology, and present both centralized and distributed algorithms for computing time-optimal convergecast schedules. Our scheme is memory-efficient as each node buffers at most one packet at any time. We evaluate our scheme in simulation and on real hardware, and show that our scheme can achieve a throughput of 203 kbit/s (86.4% of the theoretical upper bound): up to 86.24 % improvement compared with traditional TDMA-based convergecast. With an optimal routing tree and the maximum MAC layer payload, convergecast in a network with 20 sensor nodes can be completed in only 100ms.
This paper studies the problem of joint routing and transmission scheduling for reliable real-time communication over lossy networks. We impose a strict latency bound on the packet delivery from source to destination and develop transmission scheduling policies that maximize the probability that the packet is delivered within the specified deadline. A solution to this problem allows to characterize the set of achievable latencies and packet loss probabilities for a given network. We develop dynamic programming-based solutions for deadline-constrained maximum reliability routing under Bernoulli and Gilbert-Elliot packet loss models. Particular instances of the problem that admit numerically efficient solutions are discussed and our results are demonstrated on several examples.