A ferry-assisted solution for forwarding function in Wireless Sensor Networks

Oualhaj, Omar Ait; Kobbane, Abdellatif; Sabir, Essaïd; Ben‐Othman, Jalel; Erradi, Mohammed

doi:10.1016/j.pmcj.2015.05.003

Cited by 11 publications

(4 citation statements)

References 12 publications

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“…The wide adoption of WSN can improve communication and businesses in a smart environment. For instance, a WSN project that uses bus infrastructure has been adopted in India and Cambodia to provide villagers with the access to Internet services (Oualhaj et al, 2015).…”

Section: Wsnmentioning

confidence: 99%

The role of big data in smart city

Hashem

Chang

Anuar

et al. 2016

International Journal of Information Management

895

395

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The expansion of big data and the evolution of Internet of Things (IoT) technologies have played an important role in the feasibility of smart city initiatives. Big data offer the potential for cities to obtain valuable insights from a large amount of data collected through various sources, and the IoT allows the integration of sensors, radiofrequency identification, and Bluetooth in the real-world environment using highly networked services. The combination of the IoT and big data is an unexplored research area that has brought new and interesting challenges for achieving the goal of future smart cities. These new challenges focus primarily on problems related to business and technology that enable cities to actualize the vision, principles, and requirements of the applications of smart cities by realizing the main smart environment characteristics. In this paper, we describe the existing communication technologies and smart-based applications used within the context of smart cities. The visions of big data analytics to support smart cities are discussed by focusing on how big data can fundamentally change urban populations at different levels. Moreover, a future business model that can manage big data for smart cities is proposed, and the business and technological research challenges are identified. This study can serve as a benchmark for researchers and industries for the future progress and development of smart cities in the context of big data.

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Section: Wsnmentioning

confidence: 99%

The role of big data in smart city

Hashem

Chang

Anuar

et al. 2016

International Journal of Information Management

895

395

View full text Add to dashboard Cite

show abstract

“…Without loss of generality, we consider a mobile DTN with one source s i , one destination d i and n relay nodes. Relay nodes are equipped with a wireless interface allowing communication with other mobiles in their proximity . Information (data) are generated at the source nodes and need to be delivered to the destination nodes.…”

Section: System Model Analysismentioning

confidence: 99%

“…Relay nodes are equipped with a wireless interface allowing communication with other mobiles in their proximity. 1,5 Information (data) are generated at the source nodes and need to be delivered to the destination nodes.…”

Section: Wireless Energy Transfer Reward-based Mechanismmentioning

confidence: 99%

“…Delay‐Tolerant Network (DTN) paradigm is mainly addressed to interplanetary networks to deal with frequent disruptions, disconnection, and high delays. Yet, the DTN field has strongly and quickly expanded to cover other types of networks such as mobile ad hoc networks, vehicular networks, and wireless sensor networks . As such, DTN is employed as a mean to exchange data packet without the need of dedicated network infrastructure .…”

Section: Introductionmentioning

confidence: 99%

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Mobile delay‐tolerant networks with energy‐harvesting and wireless energy transfer cooperation

Oualhaj

Kobbane

Ben‐Othman

2018

Concurrency and Computation

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Summary We consider a mobile delay‐tolerant networks (MDTNs) with energy‐harvesting capabilities. In order to determine energy management policies that will improve network capacity and packet delivery ratio and maximize the system throughput, we consider a source node that seeks to send packets to a destination node. The optimal policy for the source varies according to its system state, which allows it to guarantee a maximum delivery probability rate. Our problem is modeled by decision theory; as a start, we are interested in the MDP to model and solve such sequential decision problems. Our goal is to optimize for each node, a utility depending on a random environment and decisions made by the node. As the MDP formalism reaches its limits when it is necessary to take into account the interactions between different several nodes, we will start using the graph‐based MDP where the state and action spaces are factorizable by variables. The transition functions and rewards are then decomposed into local functions and the dependency relations between the nodes are represented by a graph. To calculate the optimal policy, we propose Mean Field Approximation (MFA) and Approximate linear‐programming (ALP) algorithms for solving GMDP problem.

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Distributed duty cycle control for delay improvement in wireless sensor networks

Chen

Liu

et al. 2016

Peer-to-Peer Netw. Appl.

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A ferry-assisted solution for forwarding function in Wireless Sensor Networks

Cited by 11 publications

References 12 publications

The role of big data in smart city

The role of big data in smart city

Mobile delay‐tolerant networks with energy‐harvesting and wireless energy transfer cooperation

Distributed duty cycle control for delay improvement in wireless sensor networks

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