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Virtual Traffic Lights (VTLs) come under the umbrella of Vehicular Adhoc Networks (VANETs) and are self-organized systems to implement traffic light control systems at a road intersection. During a VTL lifetime, VTLs may fail to maintain the uninterrupted working of the traffic light system. The vehicles arriving after a stable cluster formation and ongoing operation of VTL may go unattended which can weaken its application effect. If a new vehicle approaches the intersection, it either needs to get re-clustered with the current VTL cluster or has to form a new cluster with other arriving vehicles. In this paper, we aim to incorporate the Positive Selection Algorithm (PSA) scheme which is flourished with Artificial Immune System (AIS) behaviour to detect and control this anomalous clustering condition of the VTL traffic management systems. We propose the Adaptive Layer Positive Selection Algorithm (ALPSA) for monitoring the participating and non-participating vehicles; which are detected by appropriate detectors, generated through the algorithm. The algorithm works in layers and has two phases. Prior to the algorithm, we present a mobility model to generate the metrics for appropriate clustering. We extensively evaluate the ALPSA where results validate the management with reduced 'similarity detection time' and better 'similarity detection rate'. The similarity detection time is the response time given to the vehicles to decide whether to join the VTL cluster or not. Therefore, reduction in this time has shown better working for VTLs. [ABSTRACT FROM AUTHOR]

Virtual Traffic Lights (VTLs) come under the umbrella of Vehicular Adhoc Networks (VANETs) and are self-organized systems to implement traffic light control systems at a road intersection. During a VTL lifetime, VTLs may fail to maintain the uninterrupted working of the traffic light system. The vehicles arriving after a stable cluster formation and ongoing operation of VTL may go unattended which can weaken its application effect. If a new vehicle approaches the intersection, it either needs to get re-clustered with the current VTL cluster or has to form a new cluster with other arriving vehicles. In this paper, we aim to incorporate the Positive Selection Algorithm (PSA) scheme which is flourished with Artificial Immune System (AIS) behaviour to detect and control this anomalous clustering condition of the VTL traffic management systems. We propose the Adaptive Layer Positive Selection Algorithm (ALPSA) for monitoring the participating and non-participating vehicles; which are detected by appropriate detectors, generated through the algorithm. The algorithm works in layers and has two phases. Prior to the algorithm, we present a mobility model to generate the metrics for appropriate clustering. We extensively evaluate the ALPSA where results validate the management with reduced 'similarity detection time' and better 'similarity detection rate'. The similarity detection time is the response time given to the vehicles to decide whether to join the VTL cluster or not. Therefore, reduction in this time has shown better working for VTLs. [ABSTRACT FROM AUTHOR]

A vehicular Ad hoc NETwork -VANET has been emerged as a novel application for revolutionizing the driving experience and optimizing the traffic flow control networks. The development of high efficiency and optimized routing protocols for VANET remains a challenging task because of characteristics like rapid topology changes, large scale sizes and frequent link disconnections. Hence investigation of security and privacy problems is required to be emphasized. This paper presents a robust and novel method for improving the security in VANET environment and to evaluate the performance of the proposed ODMRP (On Demand Multi Cast Routing Protocol). Hence the study utilized RSA (Rivest-Shamir-Adleman) based key generation integrated with the asymmetric key generation with AES (Advanced Encryption Standard) algorithm.This proposed trust based integrated algorithm for key generation introduces a novel roadside unit message to the base station that enables Road side units- RSU responsible for the verification of the authentication of the encrypted messages received from the vehicles as well as for the notification of the results to the vehicles. The performance analysis represented that the proposed ODMRP with the use of RSA and AES algorithm possess a better adaptation capacity to VANET network in accordance to packet delivery ratio and throughput. The results obtained from the study have been compared with the existing system and proved to be more efficient. [ABSTRACT FROM AUTHOR]

In contemporary urban areas, the construction speed of urban roads lags far behind the growth rate of the number of vehicles. The traffic delay caused by excessive vehicles is a major challenge for modern transportation systems. In this paper, we design an adaptive coordination traffic signal control system based on a three-level framework. In the framework, we propose a hierarchical strategy, which is helpful in avoiding possible offset conflicts and configuring the offsets reasonably. In addition, we establish a multi-intersection traffic signal control model with the goal of minimizing traffic delays. To solve the proposed model, we propose a new algorithm, called the Immune-Fireworks algorithm (IM-FWA), on the basis of the artificial immune and fireworks algorithms. Inspired by the antibody maintenance mechanism, diversity mechanism and communication mechanism of the artificial immune algorithm, IM-FWA can effectively overcome the shortcomings of the fireworks algorithm, such as its limited search range and lack of interaction among fireworks. The experiments show that the proposed model and algorithm have good practicability and that our control system can obtain a better signal timing schedule to effectively reduce traffic delays. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is an integration of smart sensing devices with connection ability for ease of communication. Introducing decision-making systems (DMSs) in the IoT for request processing improves the ease of access and service reliability for mobile end users. This paper proposes a two-level DMS for user service traffic smoothing (TS) in IoT communications. The two-level decision-making (2LDM) method employs traffic-aware queuing and minimum time scheduling processes for controlling the request message flows. The decision-making algorithm is modeled on time-dependent processing for minimizing the time delay in the queuing and request scheduling. The DMS considers the attributes associated with the cloud and devices to classify the request messages to prevent resource mapping failures. The disagreement between the request processing and cloud response is resolved optimally for improving the end user communication reliability in terms of the delay and resource mapping failures. Simulations evaluate the proposed DMS performance for the following metrics: sum rate, access delay, failure probability, response latency, and queue utilization. The results indicate that the proposed TS-2LDM outperforms the existing traffic controlling methods by improving the sum rate and queue utilization with controlled delay, failure, and response time. [ABSTRACT FROM AUTHOR]