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1. Sleeping is Efficient: MIS in O(1)-rounds Node-averaged Awake Complexity

   https://doi.org/10.1145/3382734.3405718  

   Chatterjee, Soumyottam ; Gmyr, Robert ; Pandurangan, Gopal ( July 2020 , PODC '20: Proceedings of the 39th Symposium on Principles of Distributed Computing)

   null (Ed.)

   Maximal Independent Set (MIS) is one of the fundamental problems in distributed computing. The round (time) complexity of distributed MIS has traditionally focused on the worst-case time for all nodes to finish. The best-known (randomized) MIS algorithms take O(log n) worst-case rounds on general graphs (where n is the number of nodes). Breaking the O(log n) worst-case bound has been a longstanding open problem, while currently the best-known lower bound is [EQUATION] rounds. Motivated by the goal to reduce total energy consumption in energy-constrained networks such as sensor and ad hoc wireless networks, we take an alternative approach to measuring performance. We focus on minimizing the total (or equivalently, the average) time for all nodes to finish. It is not clear whether the currently best-known algorithms yield constant-round (or even o(log n)) node-averaged round complexity for MIS in general graphs. We posit the sleeping model, a generalization of the traditional model, that allows nodes to enter either "sleep" or "waking" states at any round. While waking state corresponds to the default state in the traditional model, in sleeping state a node is "offline", i.e., it does not send or receive messages (and messages sent to it are dropped as well) and does not incur any time, communication, or local computation cost. Hence, in this model, only rounds in which a node is awake are counted and we are interested in minimizing the average as well as the worst-case number of rounds a node spends in the awake state, besides the traditional worst-case round complexity (i.e., the rounds for all nodes to finish including both the awake and sleeping rounds). Our main result is that we show that MIS can be solved in (expected) O(1) rounds under node-averaged awake complexity measure in the sleeping model. In particular, we present a randomized distributed algorithm for MIS that has expected O(1)-rounds node-averaged awake complexity and, with high probability1 has O(log n)-rounds worst-case awake complexity and O(log3.41 n)-rounds worst-case complexity. Our work is a step towards understanding the node-averaged complexity of MIS both in the traditional and sleeping models, as well as designing energy-efficient distributed algorithms for energy-constrained networks. 

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2. Achieving energy‐neutral data transmission by adjusting transmission power for energy‐harvesting wireless sensor networks

   https://doi.org/10.1002/wcm.2669  

   Tan, Qian ; An, Wei ; Han, Yanni ; Luo, Haiyan ; Liu, Yanwei ; Ci, Song ; Tang, Hui ( February 2016 , Wireless Communications and Mobile Computing)

   Recently, benefiting from rapid development of energy harvesting technologies, the research trend of wireless sensor networks has shifted from the battery‐powered network to the one that can harvest energy from ambient environments. In such networks, a proper use of harvested energy poses plenty of challenges caused by numerous influence factors and complex application environments. Although numerous works have been based on the energy status of sensor nodes, no work refers to the issue of minimizing the overall data transmission cost by adjusting transmission power of nodes in energy‐harvesting wireless sensor networks. In this paper, we consider the optimization problem of deriving the energy‐neutral minimum cost paths between the source nodes and the sink node. By introducing the concept of energy‐neutral operation, we first propose a polynomial‐time optimal algorithm for finding the optimal path from a single source to the sink by adjusting the transmission powers. Based on the work earlier, another polynomial‐time algorithm is further proposed for finding the approximated optimal paths from multiple sources to the sink node. Also, we analyze the network capacity and present a near‐optimal algorithm based on the Ford–Fulkerson algorithm for approaching the maximum flow in the given network. We have validated our algorithms by various numerical results in terms of path capacity, least energy of nodes, energy ratio, and path cost. Simulation results show that the proposed algorithms achieve significant performance enhancements over existing schemes. Copyright © 2016 John Wiley & Sons, Ltd.

    

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3. Improving Column Generation for Vehicle Routing Problems via Random Coloring and Parallelization

   https://doi.org/10.1287/ijoc.2021.1105  

   Yu, Miao ; Nagarajan, Viswanath ; Shen, Siqian ( November 2021 , INFORMS Journal on Computing)

   We consider a variant of the vehicle routing problem (VRP) where each customer has a unit demand and the goal is to minimize the total cost of routing a fleet of capacitated vehicles from one or multiple depots to visit all customers. We propose two parallel algorithms to efficiently solve the column-generation-based linear-programming relaxation for this VRP. Specifically, we focus on algorithms for the “pricing problem,” which corresponds to the resource-constrained elementary shortest path problem. The first algorithm extends the pulse algorithm for which we derive a new bounding scheme on the maximum load of any route. The second algorithm is based on random coloring from parameterized complexity which can be also combined with other techniques in the literature for improving VRPs, including cutting planes and column enumeration. We conduct numerical studies using VRP benchmarks (with 50–957 nodes) and instances of a medical home care delivery problem using census data in Wayne County, Michigan. Using parallel computing, both pulse and random coloring can significantly improve column generation for solving the linear programming relaxations and we can obtain heuristic integer solutions with small optimality gaps. Combining random coloring with column enumeration, we can obtain improved integer solutions having less than 2% optimality gaps for most VRP benchmark instances and less than 1% optimality gaps for the medical home care delivery instances, both under a 30-minute computational time limit. The use of cutting planes (e.g., robust cuts) can further reduce optimality gaps on some hard instances, without much increase in the run time. Summary of Contribution: The vehicle routing problem (VRP) is a fundamental combinatorial problem, and its variants have been studied extensively in the literature of operations research and computer science. In this paper, we consider general-purpose algorithms for solving VRPs, including the column-generation approach for the linear programming relaxations of the integer programs of VRPs and the column-enumeration approach for seeking improved integer solutions. We revise the pulse algorithm and also propose a random-coloring algorithm that can be used for solving the elementary shortest path problem that formulates the pricing problem in the column-generation approach. We show that the parallel implementation of both algorithms can significantly improve the performance of column generation and the random coloring algorithm can improve the solution time and quality of the VRP integer solutions produced by the column-enumeration approach. We focus on algorithmic design for VRPs and conduct extensive computational tests to demonstrate the performance of various approaches. 

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4. On the Accuracy of Network Synchronization Using Persistent Hourglass Clocks

   https://doi.org/10.1145/3362053.3363497  

   Çürük, Eren ; Yıldırım, Kasim Sinan ; Pawelczak, Przemyslaw ; Hester, Josiah ( January 2019 , Proceedings of the 7th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems)

   Batteryless sensor nodes compute, sense, and communicate using only energy harvested from the ambient. These devices promise long maintenance free operation in hard to deploy scenarios, making them an attractive alternative to battery-powered wireless sensor networks. However, complications from frequent power failures due to unpredictable ambient energy stand in the way of robust network operation. Unlike continuously-powered systems, intermittently-powered batteryless nodes lose their time upon each reboot, along with all volatile memory, making synchronization and coordination difficult. In this paper, we consider the case where each batteryless sensor is equipped with a hourglass capacitor to estimate the elapsed time between power failures. Contrary to prior work that focused on providing a continuous notion of time for a single batteryless sensor, we consider a network of batteryless sensors and explore how to provide a network-wide, continuous, and synchronous notion of time. First, we build a mathematical model that represents the estimated time between power failures by using hourglass capacitors. This allowed us to simulate the local (and continuous) time of a single batteryless node. Second, we show--through simulations--the effect of hourglass capacitors and in turn the performance degradation of the state of the art synchronization protocol in wireless sensor networks in a network of batteryless devices. 

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5. “Multi-Modulation Scheme for RFID-based Sensor Networks"

   https://doi.org/10.1007/978-3-030-67720-6_2  

   Z. Tian and Z.J. Haas ( January 2021 , Lecture notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering)

   Gao, H. ; Fan, P. ; Wun, J. ; Xiaoping, X. ; Yu, J. ; Wang, Y. (Ed.)

   RFID technology is playing an increasingly more important role in the Internet of Things, especially in the dense deployment model. In such networks, in addition to communication, nodes may also need to harvest energy from the environment to operate. In particular, we assume that our network model relies on RFID sensor network consisting of Wireless Identification and Sensing Platform (WISP) devices and RFID exciters. In WISP, the sensors harvest ambient energy from the RFID exciters and use this energy for communication back to the exciter. However, as the number of exciters is typically small, sensors further away from an exciter will need longer charging time to be able to transmit the same amount of information than a closer by sensor. Thus, further away sensors limit the overall throughput of the network. In this paper, we propose to use a multi-modulation scheme, which trades off power for transmission duration. More specifically, in this scheme, sensors closer to the exciter use a higher-order modulation, which requires more power than a lower-order modulation assigned to further away sensors, for the same bit error rate of all the sensors’ transmissions. This reduces the transmission time of the closer sensors, while also reducing the charging time of the further away sensors, overall increasing the total net-work throughput. The evaluation results show that the RFID sensor network with our multi-modulation scheme has significantly higher throughput as compared with the traditional single-modulation scheme. 

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