Deadline constrained scheduling for data aggregation in unreliable sensor networks

Hariharan, Srikanth; Shroff, Ness B.

doi:10.1109/wiopt.2011.5930006

Cited by 15 publications

(14 citation statements)

References 16 publications

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“…Its basic idea was to design a dynamic programming algorithm to schedule transmission time in layers with maximum weight matching in the bipartite graph. The application scene of the problem in the work by Hariharan and colleagues 4,6 was similar to the work by Hariharan and Shroff, 3 but the difference was that the amount of time slots every transmission was held was not fixed. Therefore, the scheduled variables were not only the time when every node sent the data but also the number of time slots occupied.…”

Section: Related Workmentioning

confidence: 92%

“…One was to balance aggregation delay and aggregation benefits. [2][3][4][5][6][7][8][9][10][11][12][13][14] The other was to balance the accuracy of the aggregated data and aggregation benefits. [15][16][17] The data aggregation research about delay mainly focused on two aspects, one of which was to minimize the maximum delay of all the aggregated data 2,[11][12][13][14] and the other was to maximize the amount of the aggregated data with deadline constraints.…”

Section: Related Workmentioning

confidence: 99%

“…[15][16][17] The data aggregation research about delay mainly focused on two aspects, one of which was to minimize the maximum delay of all the aggregated data 2,[11][12][13][14] and the other was to maximize the amount of the aggregated data with deadline constraints. [3][4][5][6][7][8][9][10] MDAT problem was proposed by X Chen et al 2 and was proved to be a nondeterministic polynomial time (NP)-complete problem. They designed SDA algorithm and analyzed that its approximate rate was D À 1, where D was the maximum degree of WSN graph.…”

Section: Related Workmentioning

confidence: 99%

“…At present, the research about DCDA problem had considered tree topology WSNs. [3][4][5][6][7] In the tree topology WSNs, data routing is determined, and wireless interference only exists between brother nodes. So, data transmission scheduling is not a severe task.…”

Section: Introductionmentioning

confidence: 99%

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Delay-constrained data aggregation scheduling in wireless sensor networks

Feng

Li²,

Jiang

et al. 2017

International Journal of Distributed Sensor Networks

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This article focuses on data aggregation scheduling problem with delay constraint in wireless sensor networks. Prior works on this problem have dealt with a tree topology wireless sensor network. However, in fact it is more common that the topology of wireless sensor network is graph topology. Delay-constrained data aggregation problem is formulated. To solve this problem, we propose an algorithm based on dynamic programming in the shortest path tree of the wireless sensor network. This approach classifies conflicts into two types, tree-inside conflicts and tree-outside conflicts with the aggregating tree. First, scheduling transmission time utilizes a dynamic programming algorithm. Then, transmissions with tree-outside conflicts are removed with maximum weight independent set in tree-outside conflict graph. As the scheduling performance depends on the aggregation tree, we propose another idea, simultaneous execution of aggregation tree construction and scheduling. We propose a greedy algorithm in wireless sensor networks. This approach is to maximize the number of scheduled nodes in every time slot from deadline to time slot 1. Simulation results show that greedy algorithm in wireless sensor networks outperforms dynamic programming in the shortest path tree and naive algorithm in terms of the effectiveness and the average delay.

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Section: Related Workmentioning

confidence: 92%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Delay-constrained data aggregation scheduling in wireless sensor networks

Feng

Li²,

Jiang

et al. 2017

International Journal of Distributed Sensor Networks

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show abstract

“…Typical approaches to WSNs have focused on efficient data gathering and energy-latency tradeoffs under deadline constraints (see [13]- [15]). These schemes propose algorithms for grouping smaller packets into larger ones by delaying data transmissions at the relaying nodes whenever slack times are positive with significant reductions in packet transmissions, congestion, and battery energy use.…”

Section: B Related Workmentioning

confidence: 99%

Scalable Meter Data Collection in Smart Grids Through Message Concatenation

Karimi

Namboodiri

Jadliwala

2015

IEEE Trans. Smart Grid

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Advanced metering infrastructure (AMI) initiatives are a popular tool to incorporate changes for modernizing the electricity grid, reduce peak loads, and meet energy efficiency targets. There is the looming issue of how to communicate and handle consumer data collected by electric utilities and manage limited communication network resources. Several data relay points are required to collect data distributedly and send them through a communication backhaul. This paper studies the smart meter message concatenation (SMMC) problem of how to efficiently concatenate multiple small smart metering messages arriving at data concentrator units in order to reduce protocol overhead and thus network utilization. This problem needs to deal with the added constraint that each originating message from its source may have its own stated deadline that must be taken into account during the concatenation process. This paper provides hardness results for the SMMC problem, and proposes six heuristics and evaluates them to gain a better understanding of the best data volume reduction policies that can be applied at data concentrators of AMI infrastructures. These results are further tested for feasibility under practical settings based on aspects, such as network and processing delays, tightness of application deadlines, and lossy backhaul links.Index Terms-Advanced metering infrastructure (AMI), algorithms, communication networks, data management.

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Break-and-join tree construction for latency-aware data aggregation in wireless sensor networks

Nguyen

Zalyubovskiy

et al. 2020

Wireless Netw

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Deadline constrained scheduling for data aggregation in unreliable sensor networks

Cited by 15 publications

References 16 publications

Delay-constrained data aggregation scheduling in wireless sensor networks

Delay-constrained data aggregation scheduling in wireless sensor networks

Scalable Meter Data Collection in Smart Grids Through Message Concatenation

Break-and-join tree construction for latency-aware data aggregation in wireless sensor networks

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