NeCoRPIA: Network Coding with Random Packet-Index Assignment for mobile crowdsensing

Abstract

The universal proliferation of mobiles devices, and specifically of smartphones with rich sensing capabilities, has given rise to a new fast-growing paradigm of sensing: mobile crowdsensing. Mobile crowdsensing (MCS) takes advantage of the ubiquity of the devices to process and collect information through voluntary sensing.This paper focuses on one specific issue: the challenge of decentralized data collection in MCS. While numerous techniques from managed networks can be adapted, one of the most efficient (from the energy and spectrum use perspective) is network coding. Network coding is well suited to networks with mobility and unreliability, however, practical network coding requires a precise identification of individual packets that have been mixed together. In a purely decentralized system, this requires either conveying identifiers in header along with coded information, or integrating a more complex protocol in order to efficiently identify the sources (participants) and their payloads.This paper presents a novel solution where packet indices in network coding headers are selected in a decentralized way, by simply choosing them randomly. Traditional network decoding techniques apply directly when all original packets have different indices. When this is not the case, i.e., in case of collisions of indices, specific decoding techniques are proposed. The proposed network decoding techniques are detailed and their performance evaluated on some examples.

Optimising data diffusion while reducing local resources consumption in Opportunistic Mobile Crowdsensing

“…As our proposal is focused on the diffusion messages, we review some of the MCS proposals addressing transmission issues. A large number of solutions are based on WiFi and Cellular communications [27,28], although we can also find proposals that are based on Bluetooth [29] due to its flexibility and low consumption features. Additionally, we find that most solutions opted for either a centralised topology [27] or a distributed topology [4] with only a reduced number of proposals choosing a hybrid approach [30].…”

Distributed topology design for network coding deployed networks

“…Network coding has been deployed in a variety of sensor network scenarios [22,23,42]. For example, network coding can improve the energy efficiency of a body area sensor network [42].…”

“…A robust network coding protocol is proposed for smart grids to enhance the reliability and speed of data gathering [22]. In [23], a mobile crowd-sensing scenario is considered for decentralized data collection, and network coding is deployed for energy and spectrum efficiency.…”

“…Nash's Existence Theorem [75] shows that every finite game has a mixed strategy NE, where pure strategies are chosen stochastically with certain probabilities. Since the link formation game G L pdq defined in (23) includes a finite number of nodes and a finite number of actions, it is a finite game. Therefore, a mixed strategy NE exists for this game.…”

“…As a solution to the problem of network topology design with the constraint, network coding [20,21] can be deployed [7,8]. Network coding is widely known to have several advantages, such as efficient resource usage (e.g., bandwidth and power), and improved robustness and throughput [22,23,24,25,26]. In this paper, we employ inter-session network coding [27] which combines multiple packets from different sources into a single packet before transmission [28].…”