Abstract
Frequent location updates of individual Internet of Things (IoT) devices can cause several problems (e.g., signaling overhead in networks and energy depletion of IoT devices) in massive machine type communication (mMTC) systems. To alleviate these problems, we design a distributed group location update algorithm (DGLU) in which geographically proximate IoT devices determine whether to conduct the location update in a distributed manner. To maximize the accuracy of the locations of IoT devices while maintaining a sufficiently small energy outage probability, we formulate a constrained stochastic game model. We then introduce a best response dynamics-based algorithm to obtain a multi-policy constrained Nash equilibrium. From the evaluation results, it is demonstrated that DGLU can achieve an accuracy of location information that is comparable with that of the individual location update scheme, with a sufficiently small energy outage probability.
Highlights
The Internet of Things (IoT) has been rapidly adopted all over the world [1,2,3]
We summarize the contributions of this paper as follows: (1) to the best our knowledge, this is the first work to optimize the trade-off between the accuracy of location information and the energy efficiency of IoT devices in a distributed manner; (2) the optimal location update policy can be obtained with a few iterations, which indicates that the policy can be adopted by practical systems without an excessive overhead; and (3) the presented evaluation results under various environments can provide invaluable guidelines for constructing massive machine type communication (mMTC) systems
We compare the proposed algorithm, distributed group location update algorithm (DGLU), with the following three schemes: (1) ALWAYS, where an individual IoT device always performs location update whenever it moves to another location; (2) RAND, where IoT devices randomly perform location update; (3) P-BASED, where IoT devices perform location update with probability P; and (4) LEADER, where a only group leader conducts location update whenever it moves to another location
Summary
The Internet of Things (IoT) has been rapidly adopted all over the world [1,2,3]. We propose a distributed group location update algorithm (DGLU) for massive machine type communication (mMTC). Excessively redundant location updates decrease the energy efficiency of IoT devices To optimize this trade-off, we formulate a constrained stochastic game model that can be converted into an equivalent linear programming (LP). The evaluation results show that DGLU can achieve an accuracy of location information that is comparable with the individual location update scheme while controlling the energy outage probability below the desired level. We summarize the contributions of this paper as follows: (1) to the best our knowledge, this is the first work to optimize the trade-off between the accuracy of location information and the energy efficiency of IoT devices in a distributed manner (i.e., based on a constrained stochastic game);.
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