Abtin Keshavarzian

Wakeup scheduling in wireless sensor networks

A large number of ractical sensing and actuating applications require immediate notification of rare but urgent events and also fast delivery of time sensitive actuation commands. In this a er,we consider the design of efficient wakeup scheduling schemes for energy constrained sensor nodes that adhere to the bidirectional end-to-end delay constraints posed by such applications. We evaluate several existing scheduling schemes and propose novel scheduling methods that outperform existing ones.We also resent a new family of wakeu methods,called multi-parent schemes, which take a cross-layer a roach where multiple routes for transfer of messages and wakeup schedules for various nodes are crafted in synergy to increase longevity while reducing message delivery latencies. We analyze the power-delay and lifetime-latency tradeoffs for several wakeup methods and show that our proposed techniques significantly improve the performance and allow for much longer network lifetime while satisfying the latency constraints.

Wi-Fi enabled sensors for internet of things: A practical approach

The vision of Internet of Things calls for connectivity not only to consumer electronics and home appliances, but also to small battery powered devices which cannot be recharged. Such small devices, often various types of sensors and actuators, are required to sustain reliable operation for years on batteries even in the presence of heavy interference. The IEEE 802.11 standard has established itself as one of the most popular wireless technologies offering connectivity. Using commercially available chips, we demonstrate the feasibility of low-power Wi-Fi technology to enable IP connectivity of battery powered devices. Three typical sensor application scenarios are investigated. We evaluate the power consumption of Wi-Fi enabled devices for each of the scenarios, investigate the impact of interference, and measure the range performance.

Near-lifetime-optimal data collection in wireless sensor networks via spatio-temporal load balancing

In wireless sensor networks, periodic data collection appears in many applications. During data collection, messages from sensor nodes are periodically collected and sent back to a set of base stations for processing. In this article, we present and analyze a near-lifetime-optimal and scalable solution for data collection in stationary wireless sensor networks and an energy-efficient packet exchange mechanism. In our solution, instead of using a fixed network topology, we construct a set of communication topologies and apply each topology to different data collection cycles. We not only use the flexibility in distributing the traffic load across different routes in the network (spatial load balancing), but also balance the energy consumption in the time domain (temporal load balancing). We show that this method achieves an average energy consumption rate very close to the optimal value found by network flow optimization techniques. To increase the scalability, we further extend our solution such that it can be applied to networks with multiple base stations where each base station only stores part of the network configuration, cooperating with each other to find a global solution in a distributed manner. The proposed methods are analyzed and evaluated by simulations.

From Experience with Indoor Wireless Networks: A Link Quality Metric that Captures Channel Memory

With ARQ based link-layer schemes, energy consumption on a link increases with packet retransmissions. We define the inefficiency of a link as the expected number of transmissions before a packet is successfully received on that link. Memory in the packet success process, caused by long indoor coherence times, strongly influences inefficiency. Based on measurements, we build a simple model for the packet success process that incorporates memory and predicts our metric practically and accurately. In particular, inefficiency is asymptotically linear in the memory duration when there is a nonzero probability of a deep fade, and approximately logarithmic otherwise.

Multi-Cluster Multi-Parent Wake-Up Scheduling in Delay-Sensitive Wireless Sensor Networks

Immediate notification of urgent but rare events and delivery of time sensitive actuation commands appear in many practical wireless sensor and actuator network applications. Multi-parent wake-up scheduling was presented as a technique which can provide bi-directional end-to-end latency guarantees while optimizing the node battery lifetime. This method takes a cross-layer approach where multiple routes for transfer of messages and wake-up schedules for nodes are crafted in synergy to reduce overall message latencies. In this paper, we generalize the multi-parent method to support a multi-cluster model for the network where we assume that the network has multiple central points called cluster-head (CH) that are in charge of scheduling the nodes in the network. A key step in multi-parent method is to divide the nodes in network into disjoint groups such that each node has at least one link to a node in each group. We formulate this step as a graph coloring problem which is shown to be NP-complete. We propose an algorithm where all the cluster-heads cooperate to find a heuristic solution for the graph coloring optimization problem in a distributed manner. We show that each cluster-head requires less memory and computational power compared to the case where one cluster-head finds the global solution, therefore the solution is very scalable.