A hybrid data aggregation scheme for provisioning Quality of Service (QoS) in Internet of Things (IoT)

Rahman, Hafizur; Ahmed, Nurzaman; Hussain, Md. Iftekhar

doi:10.1109/ciot.2016.7872917

Cited by 13 publications

(11 citation statements)

References 8 publications

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“…Authors in [3] proposed hybrid Quality of Service-Aware Data Aggregation (QADA) scheme that is a combination between the data aggregation of the cluster nodes and the aggregation of the tree nodes to overcome the limitations in both existing tree and cluster aggregation processes in order to reduce the power consumption and increase the network lifetime. QADA architecture model of the 101 nodes are designed and simulated using NS2.35 network simulator, compared to the existing tree and cluster aggregation techniques to prove the concept.…”

Section: The Node-based Aggregationmentioning

confidence: 99%

“…Thus, the N-sensor/M-node model is typed into Single-node type (N=M) and Multi-node type (N≠M, M=1) as seen in Figure 1. Like the previous works [3][4][5][6][7][8][9], the Single-node type collaborates the data traffic from M source nodes into the sink node. On the other hand, the Multi-node type can collect the data traffic from N sensors of the same source node into the sink node.…”

Section: Space Domain Attributementioning

confidence: 99%

“…The data aggregation can accurately summarize and combine multiple stream data into one data chunk to reduce the number of packets to be sent in the large scale networks [2,3].…”

Section: Introductionmentioning

confidence: 99%

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Traffic Aggregation Techniques for Optimizing IoT Networks

Ibrahim¹,

Youssef²,

Abouelatta³

2021

Adv. sci. technol. eng. syst. j.

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Internet of Things (IoT) is changing the world through a new wave of revolution for communications technologies that are no more limited to the human being. One of the main challenges that result from the exponential spread of IoT technology is the difference in the traffic characteristics between classical human communications and advanced things communications. The IoT traffic characteristics become essential for understanding and studying the parameters affecting the IoT traffic shape and thus all further studies related to traffic aggregation, topologies, and architecture designs. In this paper, a traffic aggregation in both the space domain and time domain is proposed whereas a matrix of traffic parameters is analyzed and simulated through building a practical lab case study to demonstrate the theoretical results. It is proven that the two proposed aggregation techniques could impact the traffic profile shaping existing IoT use cases for optimizing the network efficiency from several perspectives as 20% high throughput gain, 45% low collision probability, network congestion is limited to 800~1600 packets in the space domain and about 300~20 packets in the time domain, and overheads are minimized by about 50~27 Kbytes in the space domain and 9.5~0.59 Kbytes in the time domain.

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Section: The Node-based Aggregationmentioning

confidence: 99%

Section: Space Domain Attributementioning

confidence: 99%

See 1 more Smart Citation

Traffic Aggregation Techniques for Optimizing IoT Networks

Ibrahim¹,

Youssef²,

Abouelatta³

2021

Adv. sci. technol. eng. syst. j.

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“…In each iteration of the PSO algorithm, it is necessary to check the constraints in Equation (7). A PSO assisted by a proportional technique is introduced in this paper to reduce this extra computational cost in such a way to increase the convergence speed of the algorithm.…”

Section: The Proposed Pso Algorithmmentioning

confidence: 99%

Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things

2017

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Abstract:Energy efficiency is a fundamental requirement for a wireless protocol to be suitable for use within the Internet of Things. New technologies are emerging aiming at an energy-efficient communication. Among them, Bluetooth Low Energy is an appealing solution. Recently, the specifications of Bluetooth 5 have been presented with the purpose to offer significant enhancements compared to the earlier versions of the protocol. Bluetooth 5 comes with new communication modes that differ in range, speed, and energy consumption. This paper proposes a fuzzy-based solution to cope with the selection of the communication mode, among those introduced with Bluetooth 5, that allows the best energy efficiency. This communication mode, used by mobile devices, is dynamically regulated by varying the transmission power, returned as the output of a Fuzzy Logic Controller (FLC). A Particle Swarm Optimization (PSO) algorithm is presented to achieve the optimal parameters of the proposed FLC, i.e., optimizing the triangular membership functions, by varying their range, to reach the best results concerning the battery life of mobile devices. The proposed FLC is based on triangular membership functions because they represent a good trade-off between computation cost and efficiency. The paper presents a detailed description of the FLC design, a logical analysis of the PSO algorithm for the derivation of best performance conditions values, and experimental assessments, obtained through testbed scenarios.

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“…Regardless of the adopted model, ensuring integrity and confidentiality in IoT is also important to reduce the amount of bogus data on the network and cloud. Several solutions had been proposed to combat the aforementioned issues 5‐18 . However, the resource constraints of IoT and bandwidth limitation of its communication network made the adoption of some of them infeasible 3,9,13,16 .…”

Section: Introductionmentioning

confidence: 99%

A secure and collaborative data aggregation scheme for fine‐grained data distribution and management in Internet of Things

Olakanmi

Odeyemi²

2020

Security and Privacy

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One of the greatest threats to the Internet of Things (IoT) is the increase in the number of IoT devices, leading to an exponential increase in the traffics on the communication networks. Asides this, the recent rise in ransomware, which is becoming better at evading detection, is posing security and privacy threats on IoT. With these, there is a need for effective security and aggregation solutions capable of securing data, protecting privacy, and minimizing traffic on the networks. Most of the existing security approaches are network and application‐centric and not effective for IoT due to the heterogeneity and resource constraints of its devices. To address these, we propose a security and aggregation solution, which not only reduces the traffic on the communication network but also enforces integrity and confidentiality on IoT. Our scheme is capable of securing, aggregating, and separating heterogeneous IoT devices' data. Besides, the scheme can detect and filter injected false data during in and out‐of‐network data access through the location‐based parametric‐attribute. Security and performance analysis show that our proposed scheme is secure and efficient.

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A hybrid data aggregation scheme for provisioning Quality of Service (QoS) in Internet of Things (IoT)

Cited by 13 publications

References 8 publications

Traffic Aggregation Techniques for Optimizing IoT Networks

Traffic Aggregation Techniques for Optimizing IoT Networks

Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things

A secure and collaborative data aggregation scheme for fine‐grained data distribution and management in Internet of Things

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