Fast node cardinality estimation and cognitive MAC protocol design for heterogeneous machine-to-machine networks

Abstract

Machine-to-Machine (M2M) networks are an emerging technology with applications in numerous areas including smart grids, smart cities, vehicular telematics, and healthcare. In this paper, we design two estimation protocols for rapidly obtaining separate estimates of the number of active nodes of each traffic type in a heterogeneous M2M network with T types of M2M nodes (e.g., those that send emergency, periodic, normal type data etc), where T ≥ 2 is an arbitrary integer. One of these protocols, Method I, is a simple scheme, and the other, Method II, is more sophisticated and performs better than Method I. Also, we design a medium access control (MAC) protocol that supports multi-channel operation for a heterogeneous M2M network with an arbitrary number of types of M2M nodes, operating as a secondary network using Cognitive Radio technology. Our Cognitive MAC protocol uses the proposed node cardinality estimation protocols to rapidly estimate the number of active nodes of each type in every time frame; these estimates are used to find the optimal contention probabilities to be used in the MAC protocol. We compute a closed form expression for the expected number of time slots required by Method I to execute as well as a simple upper bound on it. Also, we mathematically analyze the performance of the Cognitive MAC protocol and obtain expressions for the expected number of successful contentions per frame and the expected amount of energy consumed. Finally, we evaluate the performances of our proposed estimation protocols and Cognitive MAC protocol using simulations.

Rapid Node Cardinality Estimation in Heterogeneous Machine-to-Machine Networks

“…We design two estimation schemes to rapidly obtain separate estimates of the number of active nodes of each data type in a heterogeneous M2M network with T types of nodes. Both these schemes outperform the schemes proposed in our prior work [16], [17] (see Section II for details).…”

“…To the best of our knowledge, in prior literature there is only one work, viz., our prior work [16], [17], which designs node cardinality estimation schemes for heterogeneous M2M networks. We have shown in this paper, via simulations, that the estimation schemes proposed in this paper significantly outperform those in [16], [17] in terms of the number of time slots required to execute for achieving a given level of estimation accuracy.…”

“…To the best of our knowledge, in prior literature there is only one work, viz., our prior work [16], [17], which designs node cardinality estimation schemes for heterogeneous M2M networks. We have shown in this paper, via simulations, that the estimation schemes proposed in this paper significantly outperform those in [16], [17] in terms of the number of time slots required to execute for achieving a given level of estimation accuracy. Intuitively, this is because the former (respectively, latter) are designed by extending the SRC S protocol [18] (respectively, LoF based protocol [19])2 for node cardinality estimation in a heterogeneous network, and the SRC S protocol [18] has been shown to outperform the LoF based protocol [19] in [18] in terms of the number of time slots required to execute.…”

“…There has been extensive research on the problem of node cardinality estimation in M2M networks and in Radio Frequency Identification (RFID) systems (see Section II for a review of these papers); however, with the exception of our prior work [16], [17],1 all the papers in the existing research literature address the problem of node cardinality estimation in a homogeneous network, i.e., a network consisting of only one type of nodes. In contrast, in this paper, we address the problem of obtaining separate estimates of the number of active nodes of each type in a heterogeneous network, i.e., a network with multiple types of nodes.…”

“…• We mathematically analyze the expected number of time slots required by HSRC-1 to execute and the expected energy consumption of a node under the scheme. • We evaluate the performances of both the proposed estimation schemes, HSRC-1 and HSRC-2, via extensive simulations and show that they require significantly fewer time slots to execute than the estimation scheme in which the SRC S protocol is separately executed T times to estimate the cardinalities of the T node types, as well as the estimation schemes proposed in [16], [17], even though all these schemes obtain estimates with the same accuracy. The rest of this paper is organized as follows.…”