Randomized dining philosophers to TDMA scheduling

In energy-harvesting sensor networks, limited ambient energy from environment necessitates sensor nodes to operate at a low-duty-cycle, i.e., they communicate briefly and stay asleep most of time. Such low-duty-cycle operation leads to orders of magnitude longer communication delays in comparison with traditional always-active networks, imposing a new challenge in many time-sensitive sensor network applications (e.g., tracking and alert). In this paper, we introduce novel solutions for bounding sink-to-node communications in energy-harvesting sensor networks. We first present an optimal solution for the sink-to-one case and its distributed implementation. For the sink-to-many case, we theoretically prove its NP-Hardness and in approximability property, followed by an efficient heuristic solution. We have evaluated our design with both extensive simulation and a TinyOS/Mote based implementation. Compared with an improved version of a state-of-the-art design, our delay maintenance design effectively provides E2E delay guarantees while consuming as much as 60% less energy.

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Bounding Communication Delay in Energy Harvesting Sensor Networks

In many sensor network applications, multiple data forwarding tasks usually exist with different source-destination node pairs. Due to limitations of the duty-cycling operation and interference, however, not all tasks can be guaranteed to be scheduled within their required delay constraints. We investigate a fundamental scheduling problem of both theoretical and practical importance, called multi-task schedulability problem, i.e., given multiple data forwarding tasks, to determine the maximum number of tasks that can be scheduled within their deadlines and work out such a schedule. We formulate the multi-task schedulability problem, prove its NP-Hardness, and propose an approximate algorithm with analysis on the performance bound and complicity. We further extend the proposed algorithm by explicitly altering duty cycles of certain sensor nodes so as to fully support applications with stringent delay requirements to accomplish all tasks. We then design a practical scheduling protocol based on proposed algorithms. We conduct extensive trace-driven simulations to validate the effectiveness and efficiency of our approach with various settings.

Understanding Multi-Task Schedulabilityin Duty-Cycling Sensor Networks

In many sensor network applications, sink node needs to actively communicate with other sensor nodes in order to perform data forwarding operations. For those applications, there is usually adelay-bounded associated with them and require the messages sent to be received within a designated time bound. In energy harvesting sensor networks, limited energy from environment necessitates sensor nodes to operate at alow-duty-cycle. Sensor nodes work active briefly and stay asleep most of time. Such low-duty-cycle operation leads to communication delays in comparison with the always-active networks. In this paper, we address the data forwarding problems in an energy harvesting sensor network where energy efficiency and data freshness need to be balanced. To solve this problem, we propose autility-based delay bounded scheme for data forwarding MaxOpUtility-based scheme. MaxOpUtility scheme offers the ability to increase reliability through relay nodes selection as well as to ensure the timeliness. In add...

Delay-Bounded Data Forwarding in Low-Duty-Cycle Sensor Networks

Low-duty-cycle mechanisms can reduce the energy consumption in wireless sensor networks. Many related researches have been made in recent years. In the low-duty-cycle environment, the latency of sending packets from a sink to each node is much longer than traditional WSNs because nodes stay asleep most of the time. In this paper, the Centralized Cluster-based Location Finding (CCLF) algorithm is proposed to reduce the high latency in low-duty-cycle WSNs by finding a suitable position for the sink. The algorithm mainly consisted of three steps: (1) Cluster construction, (2) The fast look-up table (FLU-table) construction, and (3) Sink location decision. The simulation results show that the performance of the CCLF algorithm approaches the performance of the optimal algorithm. Moreover, the CCLF algorithm requires less operation time compared with the optimal algorithm.

Reducing Communication Delay by Finding Sink Location in Low-Duty-Cycle Wireless Sensor Networks

As the R&D experience accumulates, there is a rising interest of wireless sensor network (WSN) deployment in the urban environment. For mission critical applications such as healthcare and workplace safety, in particular, it is essential that the data dissemination mechanisms satisfy two important quality of service (QoS) requirements: (1) high delivery rate and (2) low transmission delay. Proposed in this work is a cross-layer designed data dissemination mechanism, referred to as Cross-Layer Diffusion (XD), in which notions in the path discovery (routing) component are exploited by data forwarding (MAC) component to improve the delivery rate and transmission delay. Using traces collected from a prototype WSN deployed in urban environment, we compare XD to the state-of-the-art mechanisms and find that XD is not only more efficient but also more practical.

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Chieh-Ting Huang

Papers

XD: A Cross-Layer Designed Data Collection Mechanism for Mission-Critical WSNs in Urban Buildings