Towards Energy and Performance-aware Geographic Routing for IoT-enabled Sensor Networks

Hameed, Ahmad Raza; Islam, Saif ul; Raza, Mohsin; Khattak, Hasan Ali

doi:10.1016/j.compeleceng.2020.106643

Cited by 26 publications

(17 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our strategy is compared with other two routing schemes: IACO 37 and EEG. 38 In our simulations, the network size varies from 100 m × 100 m to 200 m × 200 m. The initial energy of each node is set as ε = 5.0 J. The ratio of the average residual energy to the initial energy is set as λ 1 = 0.2, λ 2 = 0.25, other parameters are set as: a 1 ∈ [0,1], a 2 ∈ [0,1], a 1 + a 2 = 1; b 1 ∈ [0,1], b 2 ∈ [0,1]; b 1 + b 2 = 1.…”

Section: Discussionmentioning

confidence: 99%

“…Three factors are considered to select paths: the communication distance of nodes, the transmission direction, and the residual energy of nodes. Hameed et al 38 devised an energy-efficient geographic (EEG) routing protocol for improving throughput, saving energy overhead, and balancing energy consumption. Three kinds of energy have been considered for building routing: residual energy, transmission energy, and receiving energy.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

GLBR: A novel global load balancing routing scheme based on intelligent computing in partially disconnected wireless sensor networks

Sun

Liao

Zeng

et al. 2022

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

Load balancing is of great significance to extend the longevity of wireless sensor networks, due to the inherent imbalanced energy overhead in such networks. However, existing solutions cannot balance the load distribution in partially disconnected wireless sensor networks. For example, if a network is partitioned into several segments with different area sizes, some areas have much more traffic load than other areas. In this article, we propose a load-balanced routing scheme, which aims to balance energy consumption within each segment and among different segments. First, we adopt unequal transmission distances to build initial routing for intrasegment load balancing. Second, we adopt the genetic algorithm to build extra routing between different segments for intersegment load balancing. The unique character of our work is twofold. On one hand, we investigate partitioned wireless sensor networks where there are several isolated segments. On the other hand, we pursue load balancing from a global perspective rather than from a local one. Some simulations verify the effectiveness and the advantages of our scheme in terms of extra deployment cost, system longevity, and load balancing degree.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

GLBR: A novel global load balancing routing scheme based on intelligent computing in partially disconnected wireless sensor networks

Sun

Liao

Zeng

et al. 2022

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…They make use of the data obtained to determine the intruders and arrive at a conclusive decision. To secure RPL against neighbouring attacks, sinkholes and ranks, a hybrid methodology is used by [10].…”

Section: Related Workmentioning

confidence: 99%

June 2021

2021

JITDW

View full text Add to dashboard Cite

IoT objects that have a resource constrained nature resulting in a number of attacks in the routing protocol for lossy networks and low-power networks. RPL is very vulnerable to selfish behaviours and internal attacks though they are built with encryption protection to secure messages. To address this vulnerability, in this paper, we propose a novel trustworthiness methodology based on metric for incorporating trust evaluation, enhancing the robustness of security mechanism. Simulation results indicate that the proposed work is efficient in terms of throughput, nodes' rank changes, energy consumption and packet delivery ratio. Moreover, using mathematical modelling, it has been observed that this methodology meets the demands of loop-freeness, optimality and consistency. This shows that this metic has both monotonicity and isotonicity requirements to enable the routing protocol. Incorporating the concepts of game theory, we can use this technique as a strategy to iterate Prisoner's Dilemma. Both evolutionary simulation and mathematical analysis indicate that the proposed metric-based routing protocol is an efficient technique in promoting evolution and stability of the IoT network.

show abstract

“…As it does not use control packets to establish a path, the geographic routing reduces routing control overhead flooded in the network to maintain network connectivity compared with other types of routing protocols. So, the areas which make the best use of communications between neighboring nodes are those where geographic protocols can be successfully applied; this is the case with the Internet of Things (Iot) [35][36][37] and the Vehicular Ad hoc Networks (VANETs) [38] among others.…”

Section: Related Workmentioning

confidence: 99%

IEGGR: Improved Energy-aware and Delivery Guarantee Geographic Routing

Redjimi

Boulaiche

Redjimi

2021

JCOMSS

View full text Add to dashboard Cite

Wireless Sensor Networks are a set of sensor nodes that probe their surroundings and send their data over multi-hop routes to a base-station (BS) for processing. Many routing protocols have been developed for WSNs. A great attention has been given to geographic routing protocols, which rely only on local knowledge of nodes to disseminate data towards the BS. In this paper, we propose a new energy efficient geographic routing protocol called Improved Energy-aware and delivery Guarantee Geographic Routing protocol (IEGGR). The proposed protocol exploits the positions of neighboring nodes, which are closest to the BS to forward packets through the shortest path in terms of energy consumption. IEGGR introduces a mechanism in order to forward packets efficiently around voids. IEGGR algorithm considers the WSN as a connected-graph and to route a packet from a source node to the BS, IEGGR tries making the locally optimal choice at each intermediate node with the hope of finding a global optimum path, which ai ms to minimize energy consumption. To find greedily the optimal path, each forwarding node exploits its neighbor positions that are closest to the BS in order to iteratively building the end-to-end optimal path. Simulation results show that IEGGR is efficient in energy management during packet forwarding.

show abstract

Towards Energy and Performance-aware Geographic Routing for IoT-enabled Sensor Networks

Cited by 26 publications

References 19 publications

GLBR: A novel global load balancing routing scheme based on intelligent computing in partially disconnected wireless sensor networks

GLBR: A novel global load balancing routing scheme based on intelligent computing in partially disconnected wireless sensor networks

June 2021

IEGGR: Improved Energy-aware and Delivery Guarantee Geographic Routing

Contact Info

Product

Resources

About