Localized Power Control for Multihop Large-Scale Internet of Things

Bader, Ahmed; Alouini, Mohamed‐Slim

doi:10.1109/jiot.2015.2464333

Cited by 11 publications

(6 citation statements)

References 31 publications

(47 reference statements)

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“…6 provides an illustration. Here, R * F = {(1, 3), (1,4), (1,5), (1,6), (1, 7), (1, 8), (2,4), (2,5), (2,6), (2,7), (2,8), (3,6), (5,4), (5, 7)}. We remark that the DISTRESS mechanism is lightweight in terms of the required synchronization and communication overhead (roughly O(|R|) per node in the worst case).…”

Section: B Multistage Play Under the Distress Mechanismmentioning

confidence: 99%

“…MAWINs embody the self-organizing network concept [1] in autonomous mobile mesh networks [2], [3], autonomous vehicular networks [4], autonomous sensor networks [5], and flying ad hoc networks [6]. In large-scale IoT systems, multi-hop cooperative relaying has been observed to improve the throughput, reliability, and energy efficiency of the data exchange between end-user devices (e.g., smart meters) and gateway nodes (e.g., data aggregation points) [7]- [11].…”

Section: Introductionmentioning

confidence: 99%

“…Being rationally motivated, easy to execute, impossible to prevent, difficult to detect, and harmful to honest nodes, TRAs call for incentive-based defense. Unfortunately, the lack of a central authority rules out common approaches based on reputation building or Stackelberg games [7], [8], [24], hence a novel game-theoretic methodology is also needed. In [25], we presented an early formulation of the multi-hop TRA problem and preliminary insights into its impact upon the nodes' cost metric.…”

Section: Introductionmentioning

confidence: 99%

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Mitigating Traffic Remapping Attacks in Autonomous Multihop Wireless Networks

Konorski¹,

Szott

2022

IEEE Internet Things J.

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Multi-hop wireless networks with autonomous nodes are susceptible to selfish traffic remapping attacks (TRAs). Nodes launching TRAs leverage the underlying channel access function to receive an unduly high quality of service (QoS) for packet flows traversing source-to-destination routes. TRAs are easy to execute, impossible to prevent, difficult to detect, and harmful to the QoS of honest nodes. Recognizing the need for providing QoS security, we use a novel network-oriented QoS metric to propose a self-enforcing game-theoretic mitigation approach. By switching between TRA and honest behavior, selfish nodes engage in a noncooperative multistage game in pursuit of high QoS. We analyze feasible node strategies and design a distributed signaling mechanism called DISTRESS, under which, given certain conditions, the game produces a desirable outcome: after an upper-bounded play time, honesty tends to become a selfish node's best reply behavior, while yielding acceptable QoS to most or all nodes. We verify these findings by Monte Carlo and ns-3 simulations of static and mobile nodes.

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Section: B Multistage Play Under the Distress Mechanismmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mitigating Traffic Remapping Attacks in Autonomous Multihop Wireless Networks

Konorski¹,

Szott

2022

IEEE Internet Things J.

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“…While numerous centralized algorithms have been proposed by researchers for minimum-power multi-hop broadcast, there does not exist much work on decentralized approaches. Recently, decentralized solutions based on blind [8] and probabilistic [10] approaches are proposed where in the former case, the nodes are unaware of the presence of each other, and in the latter one, the reception of the data is not guaranteed. Since the transmissions by such approaches are unreliable, they cannot be used for streaming applications or payment-dependent transmissions.…”

Section: State Of the Art And Main Contributionsmentioning

confidence: 99%

Energy and Social Cost Minimization for Data Dissemination in Wireless Networks: Centralized and Decentralized Approaches

Mousavi

Klein

2020

IEEE Trans. Veh. Technol.

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We study multi-hop data-dissemination in a wireless network from one source to multiple nodes where some of the nodes of the network act as re-transmitting nodes and help the source in data dissemination. In this network, we study two scenarios; i) the transmitting nodes do not need an incentive and ii) they do need an incentive and are paid by their corresponding receiving nodes by virtual tokens. We investigate two problems; P1) network power minimization for the first scenario and P2) social cost minimization for the second scenario, defined as the total cost paid by the nodes of the network for receiving data. In this paper, we propose centralized and decentralized approaches for each of the problems. The proposed decentralized approach is based on a non-cooperative cost-sharing game (CSG). In our proposed game, every receiving node chooses its respective transmitting nodes and consequently, a cost is assigned to it according to the power imposed on its chosen transmitting nodes. For the sake of energy efficiency, in our model, we employ maximal-ratio combining (MRC) at the receivers so that a receiver can be served by multiple transmitters. Moreover, besides the radio-link power, we capture the power required by the passive modules of wireless devices involved in reception/transmission. We discuss how the network is formed in a decentralized way, find the actions of the nodes in the game and show that the proposed game reaches a Nash equilibrium. To find the centralized global optimum, which is a benchmark to our decentralized approach, we use a mixed-integer-liner-program (MILP). The proposed MILP can be used for both of the problems P1 and P2 with a minor change. Simulation results show that our proposed decentralized approach outperforms the conventional algorithms in terms of energy efficiency and social cost while it can address the need for an incentive for collaboration. 1

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“…While there is strong evidence of superior performance to be attained by connectionless routing [54], there are still some open research fronts. Since the RACH area is a cornerstone in the operation of connectionless routing, it is indeed a rich area for improvement.…”

Section: Promising Directions: Multihop Networkingmentioning

confidence: 99%

Front-end intelligence for large-scale application-oriented internet-of-things

et al. 2016

Self Cite

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The Internet-of-things (IoT) refers to the massive integration of electronic devices, vehicles, buildings, and other objects to collect and exchange data. It is the enabling technology for a plethora of applications touching various aspects of our lives such as healthcare, wearables, surveillance, home automation, smart manufacturing, and intelligent automotive systems. Existing IoT architectures are highly centralized and heavily rely on a back-end core network for all decision-making processes. This may lead to inefficiencies in terms of latency, network traffic management, computational processing, and power consumption. In this paper, we advocate the empowerment of front-end IoT devices to support the back-end network in fulfilling end-user applications requirements mainly by means of improved connectivity and efficient network management. A novel conceptual framework is presented for a new generation of IoT devices that will enable multiple new features for both the IoT administrators as well as end users. Exploiting the recent emergence of software-defined architecture, these smart IoT devices will allow fast, reliable, and intelligent management of diverse IoT-based applications. After highlighting relevant shortcomings of the existing IoT architectures, we outline some key design perspectives to enable front-end intelligence while shedding light on promising future research directions.

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Localized Power Control for Multihop Large-Scale Internet of Things

Cited by 11 publications

References 31 publications

Mitigating Traffic Remapping Attacks in Autonomous Multihop Wireless Networks

Mitigating Traffic Remapping Attacks in Autonomous Multihop Wireless Networks

Energy and Social Cost Minimization for Data Dissemination in Wireless Networks: Centralized and Decentralized Approaches

Front-end intelligence for large-scale application-oriented internet-of-things

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