Proliferation of Opportunistic Routing: A Systematic Review

Dalal, Renu; Khari, Manju; Anzola, John; García‐Díaz, Vicente

doi:10.1109/access.2021.3136927

Cited by 26 publications

(15 citation statements)

References 92 publications

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“…Then, the opportunistic routing protocol based on the shortest path of end-to-end is proposed. Such as EXOR [19], SOAR [20], ROMER [21], etc. The basic idea of these kind of protocol is utilizing Dijkstra shortest path calculation method to compute the expected transmission count (ETX) value of adjacent nodes.…”

Section: Related Workmentioning

confidence: 99%

Low Energy Consumption Routing Protocol for Oil and Gas Pipeline Internet of Things

Miao

Liu

et al. 2022

Preprint

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For ensuring effective monitoring oil and gas pipelines deployed in the field or arears with poor environment, the wireless sensor network with flexibility, scalability and ease installation has become the basis of the Oil and Gas Pipeline Internet of Things (OGP-IoT). The energy limitation of sensor nodes is the key factor to restrict the performance of OGP-IoT. In addition, the end-to-end delay of the network determines the response time of OGP-IoT to pipeline accidents. It is also the key parameter to improve the real-time performance of OGP-IoT. For solving the problems of energy limitation and end-to-end delay, the Pipeline Internet of Things—Low Energy Consumption Routing Protocol (PIoT-LERP) is proposed in the paper. It can realize the energy balance of the Internet of Things by taking the remaining energy of nodes and the distance between nodes and aggregation nodes as the index of selecting candidate forwarding nodes. So, the life of network is extended and the end-to-end delay of the network is reduced by decreasing the number of data transmission hops. The simulation results show that PIoTLERP can effectively improve the network performance by extending the network life and reducing the network delay comparing with the classical opportunistic routing protocols ExOR and RE-OR.

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Section: Related Workmentioning

confidence: 99%

Low Energy Consumption Routing Protocol for Oil and Gas Pipeline Internet of Things

Miao

Liu

et al. 2022

Preprint

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“…Thus, communication opportunities are short and separated by long intervals of time; therefore, physical proximity and encounters become important to transmitting data. In an attempt to solve this issue, nodes perform the store-carryforward strategy [13]: they receive the information through physical proximity, store the messages persistently, and forward the data to the next available hop to reach the destination. Since encounters become a relevant requirement for transmissions, MONs define routing algorithms that implement the way in which the information is sent [14].…”

Section: Introductionmentioning

confidence: 99%

Improving Delivery Probability in Mobile Opportunistic Networks with Social-Based Routing

Jesús-Azabal

García-Alonso²,

Soares³

et al. 2022

Electronics

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There are contexts where TCP/IP is not suitable for performing data transmission due to long delays, timeouts, network partitioning, and interruptions. In these scenarios, mobile opportunistic networks (MONs) are a valid option, providing asynchronous transmissions in dynamic topologies. These architectures exploit physical encounters and persistent storage to communicate nodes that lack a continuous end-to-end path. In recent years, many routing algorithms have been based on social interactions. Smartphones and wearables are in vogue, applying social information to optimize paths between nodes. This work proposes Refine Social Broadcast (RSB), a social routing algorithm. RSB uses social behavior and node interests to refine the message broadcast in the network, improving the delivery probability while reducing redundant data duplication. The proposal combines the identification of the most influential nodes to carry the information toward the destination with interest-based routing. To evaluate the performance, RSB is applied to a simulated case of use based on a realistic loneliness detection methodology in elderly adults. The obtained delivery probability, latency, overhead, and hops are compared with the most popular social-based routers, namely, EpSoc, SimBet, and BubbleRap. RSB manifests a successful delivery probability, exceeding the second-best result (SimBet) by 17% and reducing the highest overhead (EpSoc) by 97%.

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“…This network permits the mobile nodes to cooperate in diversified social communication scenarios. Some of the relevant studies in this area can be seen in the works of literature (Dalal and Khari, 2021a, 2021b; Dalal et al , 2021, 2012).…”

Section: Introductionmentioning

confidence: 99%

Contact tracing and mobility pattern detection during pandemics – a trajectory cluster based approach

Nishad

Abraham

2022

IJPCC

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Purpose A wide number of technologies are currently in store to harness the challenges posed by pandemic situations. As such diseases transmit by way of person-to-person contact or by any other means, the World Health Organization had recommended location tracking and tracing of people either infected or contacted with the patients as one of the standard operating procedures and has also outlined protocols for incident management. Government agencies use different inputs such as smartphone signals and details from the respondent to prepare the travel log of patients. Each and every event of their trace such as stay points, revisit locations and meeting points is important. More trained staffs and tools are required under the traditional system of contact tracing. At the time of the spiralling patient count, the time-bound tracing of primary and secondary contacts may not be possible, and there are chances of human errors as well. In this context, the purpose of this paper is to propose an algorithm called SemTraClus-Tracer, an efficient approach for computing the movement of individuals and analysing the possibility of pandemic spread and vulnerability of the locations. Design/methodology/approach Pandemic situations push the world into existential crises. In this context, this paper proposes an algorithm called SemTraClus-Tracer, an efficient approach for computing the movement of individuals and analysing the possibility of pandemic spread and vulnerability of the locations. By exploring the daily mobility and activities of the general public, the system identifies multiple levels of contacts with respect to an infected person and extracts semantic information by considering vital factors that can induce virus spread. It grades different geographic locations according to a measure called weightage of participation so that vulnerable locations can be easily identified. This paper gives directions on the advantages of using spatio-temporal aggregate queries for extracting general characteristics of social mobility. The system also facilitates room for the generation of various information by combing through the medical reports of the patients. Findings It is identified that context of movement is important; hence, the existing SemTraClus algorithm is modified by accounting for four important factors such as stay point, contact presence, stay time of primary contacts and waypoint severity. The priority level can be reconfigured according to the interest of authority. This approach reduces the overwhelming task of contact tracing. Different functionalities provided by the system are also explained. As the real data set is not available, experiments are conducted with similar data and results are shown for different types of journeys in different geographical locations. The proposed method efficiently handles computational movement and activity analysis by incorporating various relevant semantics of trajectories. The incorporation of cluster-based aggregate queries in the model do away with the computational headache of processing the entire mobility data. Research limitations/implications As the trajectory of patients is not available, the authors have used the standard data sets for experimentation, which serve the purpose. Originality/value This paper proposes a framework infrastructure that allows the emergency response team to grab multiple information based on the tracked mobility details of a patient and facilitates room for various activities for the mitigation of pandemics such as the prediction of hotspots, identification of stay locations and suggestion of possible locations of primary and secondary contacts, creation of clusters of hotspots and identification of nearby medical assistance. The system provides an efficient way of activity analysis by computing the mobility of people and identifying features of geographical locations where people travelled. While formulating the framework, the authors have reviewed many different implementation plans and protocols and arrived at the conclusion that the core strategy followed is more or less the same. For the sake of a reference model, the Indian scenario is adopted for defining the concepts.

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Proliferation of Opportunistic Routing: A Systematic Review

Cited by 26 publications

References 92 publications

Low Energy Consumption Routing Protocol for Oil and Gas Pipeline Internet of Things

Low Energy Consumption Routing Protocol for Oil and Gas Pipeline Internet of Things

Improving Delivery Probability in Mobile Opportunistic Networks with Social-Based Routing

Contact tracing and mobility pattern detection during pandemics – a trajectory cluster based approach

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