Packet Scheduling for Real-Time Surveillance in Multihop Wireless Sensor Networks With Lossy Channels

Abstract

We consider the problem of real-time surveillance where remote sensors transmit data periodically to a control center through multihop transmissions. All data need to be delivered within a common deadline, which is the time that the control center makes control decisions. We propose a model that jointly considers the end-to-end delay constraints and delivery ratio requirements of flows, the need for multihop transmissions, and the unreliable nature of wireless transmissions. We develop a framework for designing feasibility-optimal policies. We then demonstrate the utility of this framework by considering two types of systems: one where sensors can transmit and receive packets simultaneously, possibly on different channels, and the other where sensors cannot. For the first type of systems, we propose an online distributed scheduling policy and prove that the policy is feasibility optimal. We also provide a heuristic for the second type of systems. We show that this heuristic is still feasibility optimal for some topologies. Simulation results show that both policies outperform state-of-the-art policies by large margins.Index Terms-Wireless sensor networks, multi-hop, end-to-end deadline scheduling.

On Feasibility of Multichannel Reconfigurable Wireless Sensor Networks Under Real-Time and Energy Constraints

“…The study in [44] deals with messages scheduling based on time-feasibility test. This research work is limited to a situation where real-time data packets have the same deadline, rather than checking system feasibility before adding messages.…”

“…To evaluate the effect of managing the list of active channels in this case study on the performance of aperiodic messages addition, a set of aperiodic messages is coming with the same WCTT, while messages are added sequentially according to their arrival time. As mentioned in Section IV-A, for the simulation, we choose to use a sporadic server for each channel with the proposed strategies for sending aperiodic messages (it is one of the periodic servers that are defined for adding aperiodic messages in the available slack time, see [44]). Thereafter, we run a series of simulation of the strategies that are interested in adding these messages, such as DPSC_PR/DPSC_FR and GlobalScheduler, then we plot the message addition success rate in Fig.…”

Spatial–temporal routing for supporting end-to-end hard deadlines in multi-hop networks

“…The deadline of a packet expires within the same frame in which the packet arrives. This frame-based traffic structure has been commonly assumed in the literature Hou (2015); Hou et al (2009);Jaramillo and Srikant (2011).…”

“…However, Li and Eryilmaz (2012) does not establish any performance guarantee of the proposed resource allocation policies. Hou (2015) proposed a throughput optimal policy for tree networks with a single sink node (i.e., a single destination) and frame-based traffic flows. Mao et al (2014) presented an online algorithm with throughput guarantees for general traffic flows and networks, where the competitive ratio is inversely proportional to the hops of the longest route.…”

Spatial-temporal routing for supporting end-to-end hard deadlines in multi-hop networks

“…The deadline of a packet expires within the same frame in which the packet arrives. This frame-based traffic structure has been commonly assumed in the literature Hou (2015); Hou et al (2009);Jaramillo and Srikant (2011).…”