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Congestion control model for securing internet of things data flow

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Abstract Due to enormous amount of data in emerging Internet of Things (IoT) applications, congestion control of traffic flow is very important to achieve certain level of security and Quality… Click to show full abstract

Abstract Due to enormous amount of data in emerging Internet of Things (IoT) applications, congestion control of traffic flow is very important to achieve certain level of security and Quality of Service (QoS). In the case of a congested network, the data is vulnerable of packet drop and loss, and so that the data integrity, which is a vital security issue, is degraded though it is accidental and not intentional. A Proportional Integrator Differentiator or (PID) controller is proposed in this paper and tuned with a congestion control rate based scheme for the purpose of IoT data collection. The proposed fine-tuning approach is created based on an optimization problem with an appropriate compact fine-tuning function that reflects the control requirements. In this paper, the key contribution is to implement a superior hybrid hill climbing immune algorithm to be as tuning method to secure IoT data flow. The proposed method is cheap, simple and fast. The proposed hybrid algorithm is compared with the immune-algorithm alone and proved its superiority in term of the overall tuning time. The proposed algorithm works in a cascaded way; the immune algorithm is used for rough tuning and then the hill climbing algorithm is activated for fine tuning. A straightforward network model is constructed and simulated for the goal of comparison using two control approaches, namely the single-bit indicator scheme and control scheme. The experimental results show that the proposed tuned PID controller by immune hill climbing algorithm is superior in terms of the stability of both, buffer occupancy in the switch and the source rate. The additional delay needs by securing the data is solved by the tuned PID controller. The congestion controller needs a minimum number of iterations in the tuning process to guarantee the stability and some target-accepted efficiency. The minimum number of iterations highly depends on the current forward and backward delays. It is shown that as the round-trip delay is increased, the tuning process takes longer before it reaches a stabilized and efficient controlled network. The steady-state response and the transient behavior for the PID controller are shown to be much better than the single-bit indicator scheme. Subsequently, the overall computational cost of the proposed hybrid algorithm is less than using the immune-algorithm. This is an additional feature for securing IoT data flow, which is an important contribution in this paper. The proposed scheme is better than the single-bit indicator in buffer utilization, link utilization, response to any suddenly change in the network and packet drop, which provides a highly secure system.

Keywords: data flow; congestion control; control; scheme; controller; congestion

Journal Title: Ad Hoc Networks
Year Published: 2020

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