Efficient message delivery in hybrid sensor and vehicular networks based on mathematical linear programming

Sadou, Malika; Bouallouche-Medjkoune, Louiza

doi:10.1016/j.compeleceng.2016.11.032

Cited by 21 publications

(11 citation statements)

References 11 publications

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“…Sadou and Bouallouche-Medjkoune [40] have pointed out message delivery in Hybrid Sensor and Vehicular Network (HSVN). Herein, sensor nodes are deployed between two RSU nodes.…”

Section: A Clusteringmentioning

confidence: 99%

NSSC: Novel Segment Based Safety Message Broadcasting in Cluster-Based Vehicular Sensor Network

Alkhalifa

Almogren

2020

IEEE Access

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Extensive research attention has been devoted to the Vehicular Sensor Network (VSN) owing to its great potential in environment monitoring. Still, it is difficult to diminish the broadcast storm and data collisions in vehicular senor environment. Due to improper broadcasting of safety message and transmission of packet at same time from multiple vehicles leads to collision. Our key intention is to overwhelm these shortcomings in VSN. Hence, we propose Novel Segment based Safety message broadcasting in Cluster (NSSC) based VSN. Our NSSC is mainly concentrated in three successive processes that are Cluster Formation, Collision Avoidance and Safety Message Broadcasting. Cluster formation is performed originally to sustain stable vehicular environment. Here, Variant based Clustering (VbC) Scheme is proposed to elect Cluster Head (CH) and to form clusters. CH is selected using Chaotic Crow Search (CCS) algorithm. In accord to mitigate the data collision during transmission between CH and Cluster Member, we propose Adaptive Carrier Sense Multiple Access/Collision Avoidance (Ada-CSMA/CA) protocol. Safety message broadcasting adopts Segment based Forwarder Selection (SFS) scheme which selects optimal forwarder using Fuzzy-Vikor method. In this, optimal forwarder is selected concerning to broadcast safety message which reduces the broadcast storm. In regard to validate the proposed NSSC, we have conducted simulations on Omnet++ and SUMO simulator based Veins framework. The acquired results are auspicious in terms of succeeding metrics reachability, average number of collision, duplicate data packets, latency, packet delivery ration and throughput.

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“…Sadou and Bouallouche-Medjkoune [40] have pointed out message delivery in Hybrid Sensor and Vehicular Network (HSVN). Herein, sensor nodes are deployed between two RSU nodes.…”

Section: A Clusteringmentioning

confidence: 99%

NSSC: Novel Segment Based Safety Message Broadcasting in Cluster-Based Vehicular Sensor Network

Alkhalifa

Almogren

2020

IEEE Access

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“…Moreover, an on-board mobile-app is designed for efficient, smart, and remote traffic monitoring. In [17], the authors addressed the message on time delivery problem in VANETs. The authors formulated the problem as bi-objective binary linear programming.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Priority-Based Efficient Resource Allocation and Computing Framework for Vehicular Multimedia Cloud Computing

et al. 2020

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In intelligent transportation system, smart vehicles are equipped with a variety of sensing devices those offer various multimedia applications and services related to smart driving assistance, weather forecasting, traffic congestion information, road safety alarms, and many entertainment and comfort-related applications. These smart vehicles produce a massive amount of multimedia related data that required fast and real-time processing which cannot be fully handled by the standalone onboard computing devices due to their limited computational power and storage capacities. Therefore, handling such multimedia applications and services demanded changes in the underlaying networking and computing models. Recently, the integration of vehicles with cloud computing is emerged as a challenging computing paradigm. However, there are certain challenges related to multimedia contents processing, (i.e., resource cost, fast service response time, and quality of experience) that severely affect the performance of vehicular communication. Thus, in this paper, we propose an efficient resource allocation and computation framework for vehicular multimedia cloud computing to overcome the aforementioned challenges. The performance of the proposed scheme is evaluated in terms of quality of experience, service response time, and resource cost by using the Cloudsim simulator. INDEX TERMS Intelligent transportation system, multimedia cloud computing, vehicular networks, quality of experience, multimedia contents processing, response time, smart vehicle.

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“…[12][13][14][15][16][17][18][19][20][21] Because of it, the problem of conflicting and incommensurate always exists and may not be removed.…”

Section: Motivationmentioning

confidence: 99%

“…In many real-life applications, this mapping produced a general solution to get optimal goal, which is not possible in earlier methods that are mentioned in the literature review. [12][13][14][15][16][17][18][19][20][21]…”

Section: Motivationmentioning

confidence: 99%

“…The characteristics of OE2R is compared with some existing methods (eg, EN-AODV 16 RECI, 17 EASRP, 18 LPP, 19 CLEA, 20 BLPP 21 ), which are shown in Table 2. The simulation comparison has been made with the 2 existing methods (ie, LPP 19 and BLPP 21 ). The OE2R is based on a hybrid approach that has a combined feature of several AI techniques such as MOO, GP, aspiration level, and optimset.…”

Section: Performance Evaluationmentioning

confidence: 99%

See 1 more Smart Citation

Energy efficient routing formation technique for hybrid ad hoc network using fusion of artificial intelligence techniques

Das

Tripathi

2017

Int J Communication

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Hybrid Ad-hoc NETwork (HANET) is a fusion of both the static and dynamic topologies. Each node of this network consists of low capacity battery. Because of heterogeneous characteristic of the topology, network parameters are imprecise in nature. This, in effect, the performance and lifetime of the network degrade. To overcome these issues, this paper proposes an optimized energy efficient routing (OE2R) method. This method is inspired by artificial intelligence techniques such as multiobjective optimization, geometric programming, aspiration level, and tolerance limit. The fusion of such stated artificial intelligence techniques provide an effective tool to optimize multiple conflict objectives and estimate imprecise parameters of the network, simultaneously. The proposed technique OE2R is simulated using LINGO optimization software. To justify the effectiveness of the proposed technique, its performance is compared with some existing methods such as approximate linear programming technique for average cost bounds and linear programming-based efficient message delivery approach in hybrid network in several passes of performance metrics. The simulation results show that the proposed OE2R method performs much better with the comparative methods and may be implemented as energy-efficient routing for HANET. KEYWORDSapproximation method, aspiration level, geometric programming, hybrid ad hoc network, multiobjective optimization, optimset Int J Commun Syst. 2017;30:e3340.wileyonlinelibrary.com/journal/dac

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Efficient message delivery in hybrid sensor and vehicular networks based on mathematical linear programming

Cited by 21 publications

References 11 publications

NSSC: Novel Segment Based Safety Message Broadcasting in Cluster-Based Vehicular Sensor Network

NSSC: Novel Segment Based Safety Message Broadcasting in Cluster-Based Vehicular Sensor Network

Dynamic Priority-Based Efficient Resource Allocation and Computing Framework for Vehicular Multimedia Cloud Computing

Energy efficient routing formation technique for hybrid ad hoc network using fusion of artificial intelligence techniques

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