Control Packets Research Articles

SSH-MAC: Service-Aware and Scheduling-Based Media Access Control Protocol in Underwater Acoustic Sensor Network

In the framework of the space-air-ground-ocean integrated network, the underwater acoustic sensor network (UASN) plays a pivotal role. The design of media access control (MAC) protocols is essential for the UASN to ensure efficient and reliable data transmission. From the perspective of differentiated services in the UASN, a service-aware and scheduling-based hybrid MAC protocol, named the SSH-MAC protocol, is proposed in this paper. In the SSH-MAC protocol, the centralized scheduling strategy is adopted by sensor nodes with environmental monitoring service, and the distributed scheduling strategy is adopted by sensor nodes with target detection service. Considering the time-varying data generation rate of sensor nodes, the sink node will switch the scheduling mode of sensor nodes based on the specific control packet and adjust the resource allocation ratio between centralized scheduling and distributed scheduling. Simulation results show that the performance of the SSH-MAC protocol, in terms of utilization, end-to-end delay, packet delivery ratio, energy consumption, and payload efficiency, is good.

RPL*: An Explainable AI-based routing protocol for Internet of Mobile Things

The Internet of Mobile Things (IoMT) is an emerging paradigm of Internet of Things (IoT) with special focus on enabling mobility to the ‘things’. Several IoMT applications such as group of robots or drones performing collaborative search and rescue operation, identification of mines, warehouse management, goods delivery, etc can be considered as examples of IoMT systems. In the applications mentioned above, the nodes may send the information in a multi-hop manner to the root or coordinator node which may be static or mobile. While the Routing Protocol for Low Power and Lossy Networks (RPL) is extensively utilized in static IoT networks, it encounters significant limitations in handling mobility and providing resilience against routing attacks in mobile IoT networks. In this work, we propose a modified RPL, RPL* which is robust to handling mobility in nodes and is resilient towards routing attacks. In RPL*, any deviation from the normal behaviors of the network are identified as anomalies using an unsupervised Explainable Artificial Intelligence (XAI) strategy. In RPL*, we propose a novel mobility detection mechanism that will identify the mobility in the network in an energy efficient manner without incurring additional communication overhead. To maintain the connectivity with parent node, we propose a novel proactive connectivity management mechanism in RPL* which will ensure a smooth transition from one parent to another if required, thus avoiding the network partitioning due to mobility. The performance analysis of the system has demonstrated an improvement in packet delivery ratio of the mobile nodes by 40% due to the proposed RPL* when compared to RPL. Also, the proposed XAI strategy provided an F1-score of over 95% for the detection of sink hole and black hole attacks in the tested IoMT network scenarios. It was observed that RPL* improves the performance of the IoMT network when compared to RPL. However it may be noted that the mechanisms introduced to support mobility does not lead to a drop in PDR or increase in control packet overhead for static networks. Hence, RPL* can be considered as an alternative to RPL for IoT as well as IoMT networks.

A new priority aware routing protocol for efficient emergency data transmissions in MANETs

This paper introduces a new priority-aware routing protocol for mobile Ad-hoc networks to be utilized in emergencies, which is based on AODV. Mobile Ad-hoc networks find extensive use in various domains including military operations, environmental monitoring, healthcare, disaster response, smart transportation systems, unmanned aerial vehicles, and smart homes. During emergencies, communication can be severely restricted or even impossible due to the congestion of physical communication channels and unexpected technical failures in the infrastructure. Mobile Ad-hoc networks offer a solution to maintain continuous and reliable communication under such challenging conditions. In emergency scenarios, it is crucial for any node in the network to promptly deliver urgent messages to the intended destination, especially when certain nodes require ongoing active communication. The proposed routing protocol effectively addresses this requirement through its priority-aware mechanisms. The protocol ensures that nodes not involved in emergency tasks select the least congested route to prevent any delays or disruptions in the transmission of critical emergency data. This approach guarantees seamless communication for emergency nodes while allowing non-emergency nodes to communicate with each other as well. The study proposed in this paper introduces a new priority-aware routing protocol based on AODV for mobile Ad-hoc networks in emergencies. The packet transmission ratio of emergency nodes within the network is improved while maintaining the overall network performance unaffected. The adoption of proposed mechanisms to enhance performance does not necessitate an expansion in the size of data and control packets. These mechanisms do not inflict any supplementary latency or incur packet loss expenses on the network. The proposed protocol has been implemented and evaluated using ns-3 simulation software across various emergency scenarios. The results show that emergency nodes using the proposed protocol, achieve better packet delivery ratios compared to the original AODV, DSR, P-AODV, and AOMDV protocols, with improvements of 10.8%, 15.9%, 6.2%, and 5.9% respectively. This improvement in the packet delivery ratio for emergency data traffic is achieved without causing any disruptions in the overall network communication flow.

Hot‐spot aware multicost‐based energy‐efficient routing protocol for WBANs

SummaryWireless body area networks (WBANs) are becoming widely considered in remote healthcare monitoring applications. However, WBAN nodes have limited resources; therefore, effective and reliable routing protocols are pivotal research challenges. Furthermore, balancing the traffic load among sensor nodes is also highly required to increase network stability. In recent years, many interesting routing solutions have been proposed for WBANs; however, the significant feature in terms of stability and energy in these solutions has not been sufficiently addressed. Therefore, in this context, the Hot‐Sspot Aaware Multicost‐based Energy‐efficient Routing (H‐SAMER) protocol is proposed in this paper. The suggested protocol used multieffective cost function for next‐hop node selection based on the data type, where the patient's data are categorized into three classes: normal data, on‐demand data, and emergency data. Furthermore, the H‐SAMER protocol adds awareness to the transmission of control packets by adding the cost value to the RREQ packets. Thus, the simulation scenario shows that the H‐SAMER saves energy 8.57%, 88%, 98%, 97%, and 100% greater than E‐HARP, EH‐RCP, CO‐LAEEBA, EECBSR, and ELR‐W, respectively. Moreover, the first node death of the proposed H‐SAMER is delayed to round number 7500, which proves H‐SAMER to be a stable and reliable effective solution for WBANs.

A novel swarm intelligence‐based fuzzy logic in efficient connectivity of vehicles

SummaryA vehicular ad hoc network (VANET) is a wireless network composed of a collection of mobility devices that link via a wireless channel without the need for permanent infrastructure or centralized administration. Multicasting is a method of sending data from a single node to multiple recipients at the same time. Because of its energizing network topology and constricted resources, a mobile ad hoc network (MANET) presents a number of issues. Because network execution measurements such as latency, bandwidth, throughput, and energy fluctuate so rapidly owing to node movement, these network properties in a wireless mobile ad hoc network are ambiguous. Because of the influence of these uncertainty issues, determining the top‐grade path from the originating node to a set of recipient nodes is challenging. In order to preserve network resources, we used a Swarm Intelligence‐based fuzzy logic strategy in this study that includes channel caliber factor and connection termination time to try to alleviate these uncertainty issues. This strategy integrates all of the network indicators available for the routes into an individual quantity named as fuzzy cost or cost of communication. The routes with the lowest fuzzy cost will be regarded optimum, and data will be delivered along this route from the originating point to a set of receivers. The simulation was carried out using NS‐3.38 and MATLAB, and the results reveal that the suggested protocol, HACOFLM, outperforms ODMRP, OFAODV, MAODV, and DFMCRP by means of packet delivery ratio, latency, control packet overhead, and throughput. DFMCRP outperforms MAODV by 3% to 6%, OFAODV by 13% to 19%, and ODMRP by 16% to 23%. According to HACOSMO, based on the number of vehicles and velocities, routing overhead is 7% to 10% less than DFMCRP, 9% to 13% less than MAODV, 17% to 29% less than OFAODV, and 22% to 36% less than ODMRP. It improvise throughput by 4% to 6% when contrasted to DFMCRP, 5% to 9% when contrasted to MAODV, 10% to 14% when contrasted to OFAODV, and 14% to 23% when contrasted to ODMRP.

Investigating delay of the media access control protocols for IoT‐RoF using quantum entanglement

AbstractOne of the significant challenges of the Radio over fibre (RoF) Medium Access Control (MAC) protocol is the propagation delay. This delay can lead to serious issues, such as higher propagation delay resulting in collisions and unnecessary retransmissions. Quantum entanglement is an excellent candidate to overcome the propagation delay of the RoF MAC protocol. A new quantum MAC protocol is proposed, named the Quantum Entanglement‐based MAC protocol (QE‐MAC), in which Quantum Teleportation is utilised to address the propagation delay. Four entanglement states are employed to represent the control packets of the classical MAC protocol, and data is transmitted over the classical channel. Instead of using control packets such as acknowledgement, request to send, and Clear to send, state transitions are employed. This approach avoids the delay and collision issues associated with control packets, resulting in a significant improvement in network performance. The delay, duty cycle (DC), and power consumption of the proposed QE‐MAC protocol are formulated and derived. The protocol is evaluated in terms of delay, DC, and power consumption, demonstrating superior performance compared to the classical RoF MAC protocol. In comparison to published works, our proposed approach has successfully reduced both delay and power consumption by 35%.

Towards Energy Efficient Wireless Sensing by Leveraging Ambient Wi-Fi Traffic

Wireless-based sensing of physical environments has garnered tremendous attention recently, and its applications range from intruder detection to environmental occupancy monitoring. Wi-Fi is positioned as a particularly advantageous sensing medium, due to the ubiquity of Wi-Fi-enabled devices in a more connected world. Although Wi-Fi-based sensing using Channel State Information (CSI) has shown promise, existing sensing systems commonly configure dedicated transmitters to generate packets for sensing. These dedicated transmitters substantially increase the energy requirements of Wi-Fi sensing systems, and hence there is a need for understanding how ambient transmissions from nearby Wi-Fi devices can be leveraged instead. This paper explores the potential of Wi-Fi-based sensing using CSI derived from ambient transmissions of Wi-Fi devices. We demonstrate that CSI sensing accuracy is dependent on the underlying traffic type and the Wi-Fi transceiver architecture, and that control packets yield more robust CSI than payload packets. We also show that traffic containing upload data is more suitable for human occupancy counting, using the Probability Mass Function (PMF) of CSI. We further demonstrate that multiple spatially diverse streams of Wi-Fi CSI can be combined for sensing to an accuracy of 99%. The experimental study highlights the importance of training Wi-Fi sensing systems for multiple transmission sources to improve accuracy. This research has significant implications for the development of energy-efficient Wi-Fi sensing solutions for a range of applications.

Traffic rate agnostic end-to-end delay optimization using receiver-based adaptive link scheduling in 6TiSCH networks

Link scheduling is a key component in 6TiSCH networks. It mainly specifies a node is allowed to transmit packets through which link at what time and in which channel. There exist many link scheduling schemes in the literature for 6TiSCH networks. Among the distributed schemes, the Self-healing distributed scheduling for end-to-end delay optimization (Stratum) was specifically devised to minimize end-to-end latency. However, it performs worse in case of higher traffic rates. On the other hand, the de-facto link scheduling standard Minimal Scheduling Function (MSF) allocates cells (i.e. timeslot and channel) randomly in a slotframe for scheduling transmissions, and thus its end-to-end delay performance is not good under all traffic rates. Therefore, this paper proposes a traffic rate agnostic distributed link scheduling function (RTDS) for 6TiSCH networks. The RTDS follows a receiver-based cell selection and allocation strategy to reduce the waiting time of a packet in the buffer of receiving node before forwarding the packet towards final destination. Unlike MSF, the RTDS uses lesser number of control packet exchanges to adapt the schedule of a link based on the present network condition and traffic rate. The proposed RTDS scheme minimizes end-to-end latency under any traffic rate. RTDS is implemented in the 6TiSCH simulator. Simulation results show that RTDS can significantly improve the end-to-end latency compared to the benchmark schemes. For example, in an 80-node network, the RTDS reduces end-to-end latency by 58% and 43% in low and high traffic rates, respectively, compared to that in MSF. Further, it outperforms Stratum by 77% and 75% under the low and high traffic rates, respectively.

How does Wi-Fi 6 fare? An industrial outdoor robotic scenario

Wi-Fi is a standard off-the-shelf solution for industrial robotics. The IEEE 802.11ax amendment extends it to support the 6 GHz band, 160 MHz bandwidth and bit-rates up to 9.6 Gbps. In this article, we evaluate the performance of Wi-Fi 6 compared to Wi-Fi 5 and Wi-Fi 4. We select 9 physical layers (PHYs) representing different Wi-Fi generations and we evaluate their performance in an industrial shipyard in the presence of high radio frequency interference and metallic obstructions. We deploy setup of a robotic station (STA) and a controller STA with three applications running in parallel: a robotic STA is sending a high throughput stream to a controller, a Robotic Operating System (ROS) application is sending time-critical control commands to the robotic STA, Precision Time Protocol (PTP) keeps synchronizing the clocks between both STAs. We evaluate the performance in terms of three Key Performance Indicators (KPIs): streaming throughput, IP-level delay using PTP, and Application-level delay of ROS control packets. The networks are run in: Short range Line of Sight (LoS), Medium range LoS, Long range None-LoS (NLoS), and Long range mixed settings. We note that depending on the PHY configuration, an older Wi-Fi generation may outperform Wi-Fi 6. We further observe trade-offs between the different PHYs: wide channel PHYs (e.g. 160 MHz) had best throughput reaching up to 900 Mbps while PHYs while 80 MHz or 20 MHz bandwidth achieved as low as 9 ms delay. This motivates further research in multi-PHY adaptation for KPIs specific to industrial robotics.

Evaluation of 6LoWPAN Generic Header Compression in the Context of a RPL Network.

The Internet of Things (IoT) facilitates the integration of diverse devices, leading to the formation of networks such as Low-power Wireless Personal Area Networks (LoWPANs). These networks have inherent constraints that make header and payload compression an attractive solution to optimise communication. In this work, we evaluate the performance of Generic Header Compression (6LoWPAN-GHC), defined in RFC 7400, for IEEE 802.15.4-based networks running the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). Through simulation and real-device experiments, we study the impact of 6LoWPAN-GHC on energy consumption and delays and investigate for which scenarios 6LoWPAN-GHC is beneficial. We show that all RPL control packets are compressible by 6LoWPAN-GHC, which reduces their transmission delay and as such their vulnerability to interference. However, for the devices under study transmitting at 250 kbit/s, the energy gain obtained from sending a compressed packet is outweighed by the energy needed to compress it. The use of 6LoWPAN-GHC causes an energy increase of between 2% and 26%, depending on the RPL packet type. When the range is more important than the bandwidth and a sub-GHz band is used at 10 kbit/s, an energy gain of 11% to 29% can be obtained, depending on the type of RPL control packet.

Delphi: Computing the Maximum Achievable Throughput in SD-RAN Environments

Software-Defined Radio Access Networks (SD-RANs) foster the concepts of programmability and flexibility, which are vital for next generation cellular networks. However, SD-RANs render network management and orchestration very challenging. Indeed, related works indicate that when thousands of connected devices are spread across the underlying network, SD-RAN approaches with a single controller become deficient and exhibit undesired behavior. Despite this, state-of-the-art research papers lack concrete solutions and evaluations with respect to throughput predictability, where the latter is jeopardized by irregularities in the SD-RAN control plane, specifically in realistic testbeds. In order to overcome the aforementioned issues, in this work, we present : a novel platform that provides both analytical and experimental methods to achieve our goal, which is computing the maximum achievable throughput in SD-RAN environments. Analyzing the results provided by, we can capture the impact of the SD-RAN control plane on throughput. Moreover, we can design important guidelines as to which policy to choose given objectives such as throughput maximization or robustness. Providing a platform for SD-RAN evaluations based on open-source components, enables new avenues for research in the mobile network community. Focusing on FlexRAN SD-RAN controller for our initial results, overall, our findings show that when the number of Base Stations (BSs) and User Equipment (UEs) in the network increases beyond 5000, due to non-timely received control packets for the maximum Channel Quality Indicator (maxCQI) policy the overall throughput decreases by more than 20%.

Cost-effective live video streaming for internet of connected vehicles using heterogeneous networks

Smart vehicles of Internet of Connected Vehicles (IoCV) create Ad-Hoc networks and are persistently connected to the Internet through different network access technologies like Wifi, cellular, and dedicated short range communication (DSRC). A vehicle may prefer one network access technology over another based on availability, coverage area, and network access cost. The choice also depends on application requirements, like delay-tolerant or delay-sensitive, and application objectives, like maximizing data rate, maximizing cellular traffic offloading, etc. Cellular traffic offloading using Wifi access points and vehicle-to-vehicle (V2V) collaborations are very challenging due to the intermittent short coverage areas of Wifi access points and highly dynamic connectivity of V2V Ad-Hoc network. Most existing works on traffic offloading have considered delay-tolerant or on-demand services, whereas delay-constrained live video streaming services are mostly ignored. This work is focused on live video streaming services over IoCVs, where the non-triviality of the network selection task is demonstrated by formulating the task as an integer linear programming problem (ILPP). Accordingly, a distributed algorithm is proposed, which greedily maximizes cellular traffic offloading while significantly reducing the control packet overheads. Compared to existing works, the proposed work provides the best service effectiveness with a balanced performance on traffic offloading, service efficiency, and user satisfaction.

An Approach for Scaling Down the Control Packet Load of AODV Routing by Adopting WRS Model for MANETs

An Approach for Scaling Down the Control Packet Load of AODV Routing by Adopting WRS Model for MANETs

An Energy-Efficient Multi-Channel Design for Distributed Wireless Sensor Networks

This article discusses the importance of designing an efficient medium access control (MAC) protocol for wireless sensor networks (WSNs) to optimize energy consumption at the data link layer while transmitting high traffic applications. The proposed protocol, EE-MMAC, is an energy-efficient multichannel MAC that reduces energy consumption by minimizing idle listening, collisions, overhearing, and control packet overhead. EE-MMAC utilizes a directional antenna and periodically sleep technique in a multi-channel environment. Nodes exchange control packets on the control channel to choose a data channel and decide the beam direction of the flow. Simulation results show that EE-MMAC achieves significant energy gains (30% to 45% less than comparable IEEE 802.11 and MMAC) based on energy efficiency, packet delivery ratio, and throughput.

SCHEISB: Design of a high efficiency IoMT security model based on sharded chains using bio-inspired optimizations

Securing Internet-of-Medical Things (IoMT) devices is a multidomain task that involves analysis of attack patterns from data & control packets. Existing security models either work on pre-emptive analysis, real-time analysis or post-processing analysis of different packet types. These operations add to the complexity of data processing, which reduces Quality of Service (QoS) levels of IoMT deployments. To overcome these issues, this paper proposes design of a sharded chain based high efficiency IoMT security model that uses bioinspired optimizations. The proposed model initially deploys a novel single chained Proof-of-Medical-Trust (PoMT) based consensus technique, which assists in identification of high-trust miners. The QoS levels are continuously monitored for each block request, and a Teacher–Learner based Optimization (TLbO) model is deployed to make sharding decisions. These decisions are reconfirmed by a Particle Swarm Optimization (PSO) model, which assists in estimation of shard length under different attack types. These attacks include Spoofing, Spying, and Flooding attacks, which affects the authenticity of data samples from IoT devices under real-time scenarios. The PSO Model also recommends splitting & merging decisions based on the context of IoMT deployments. The PoMT consensus is modified to support sharded chains, and assists in reducing mining delays without compromising miner trust levels. The modified PoMT consensus is capable of selecting overlapping miner nodes, while incorporating load balancing for optimal energy consumption during the mining process. Due to these enhancements, the proposed model is able to reduce mining delay by 8.5%, while reducing energy consumption by 3.2%, and reducing access delay by 4.9% under real-time clinical scenarios.

Joint Controller Placement and Control-Service Connection in Hybrid-Band Control

By separating the forwarding and control planes, Software-Defined Networking (SDN) facilitates flexible traffic routing and network management for a service network. Because of the impact of controller deployment on message transmission distances and network latency, controller placement problems have drawn many researchers' attention. However, assumptions in most existing research that all control packets are either transmitted in the service network (i.e., in-band control) or through predetermined control-service connection (i.e., out-of-band control) are not reasonable due to bandwidth resources occupation on the service network or high construction costs. In this paper, we are the first to jointly discuss the controller placement and control-service connection problem for latency minimization in the hybrid-band control mode, which is essentially a bi-level programming optimization problem. Specifically, we introduce auxiliary variables to simplify the above NP-hard problem. Next, Generalized Benders decomposition is used to obtain an optimal solution in theory. In addition, we propose a time-efficient fireworks algorithm with a little latency increment for large-scale networks. Extensive evaluations show that the two proposed algorithms accomplish the desired objectives and respectively achieve up to 35% and 25% latency decrement than greedy algorithms.

A novel scheme based on coarse‐grained localization and fine‐grained isolation for defending against Sybil attack in low power and lossy networks

AbstractDue to the lack of security mechanisms and sensor resources, the IPv6 Routing Protocol for Low power and Lossy networks (RPL) is vulnerable to various attacks, among which Sybil attack has received a lot of attention. This paper proposes a novel scheme based on coarse‐grained localization and fine‐grained isolation (CLFI) for defending Sybil attack. In CLFI, normal neighbor nodes are identified based on received signal strength indicator (RSSI). To further identify Sybil nodes, a physical address identifier called is defined, which is calculated as the difference of RSSI at two different receivers when they are receiving the same packet. In order to facilitate the calculation of , a set of anchor nodes are deployed to broadcast the received RPL control packets. Then Sybil behaviors can be detected by comparing the physical address identifier with the logical address embedded in the received packets. The proposed CLFI scheme has been completely implemented in the Contiki operating system. The extensive evaluation in comparison with the state‐of‐the‐art scheme indicates that CLFI can quickly localize and isolate Sybil nodes.

ENSING: Energy saving based data transmission in Internet of Drones for 3D connectivity in 6G networks

The Internet of Drones represents an emerging framework with a plethora of applications in the context of Beyond-5G networks. Drone technology uses are spreading from commercial, industrial up to military applications. Drones, a.k.a. Unmanned Aerial Vehicles (UAVs), are largely adopted in all those fields where men cannot reach or are unable to perform in a timely and efficient manner. Communications among UAVs are important to allow task coordination and network organization. However, as a drawback, UAVs are strongly affected by energy consumption that limits their flight and task accomplishment. In this paper, we address the energy consumption issue in UAV swarms and present a novel routing approach, namely ENSING, that aims to save energy consumption. Differently from previous approaches that simply reduce the number of control packets to save UAV battery level, ENSING approach selects the next-hop UAV forwarder according to energy constraints. In this way, only eligible UAVs with acceptable energy requirements can be selected in the packet forwarding, thus avoiding the involvement of those UAVs with limited battery level. Compared to other routing techniques, ENSING exhibits better performance in terms of packet delivery rate, throughput and latency.

A Gaming and Trust-Model-Based Countermeasure for DIS Attack on 6TiSCH IoT Networks

The 6TiSCH communication architecture provides delay-bounded packet delivery, energy-efficient and reliable data-delivering communication in mission-critical Internet of Things (IoT) applications. It uses IETF’s 6TiSCH minimal configuration (6TiSCH-MC) standard for resource allocation during network formation and routing using Routing Protocol for Low power and Lossy network (RPL) as routing protocol. In RPL, the DODAG Information Solicitation (DIS) control packet is used to solicit routing information from the existing networks. However, it is observed that malicious transmission of this DIS packet can severely affect the 6TiSCH networks in terms of nodes’ network joining time and energy consumption. Therefore, designing countermeasures of DIS attack in 6TiSCH network has become critically important. Additionally, the existing works neither considered all the possible parameters together for detecting DIS attack nor energy efficient, and create control packet overhead. In this work, we model non-cooperative gaming to determine the optimal probability of responding to a DIS packet. Subsequently, we design a trust model to detect malicious DIS transmission in 6TiSCH networks. Finally, we merge both the proposed gaming model and trust model to propose a scheme – Gaming and Trust based Counter Measure (GTCM) to reduce the effect of DIS attack in 6TiSCH networks. We implement the GTCM on Contiki-NG and validate it using open source FIT IoT-LAB testbed. Our experimental testbed results show that GTCM reduces the effect of DIS attack in terms of pledges’ (new nodes) joining time and energy consumption significantly.

Optimal Intelligent Vehicle Control System for Emergency Vehicle Using Visible Light Communication VANET

Abstract: Traffic congestion is one of the significant problems in every metropolitan city. Traffic congestion occurs, when large numbers of vehicles are all together and are not able to move or move slowly, it is also known as a traffic jam. The main aim of the proposed OIVC-VLC VANET system is to improve the data transmission rate to control traffic in high density loads for emergency vehicles. Traffic congestion leads to wasting of time, road accidents, delays of trips, and reduces regional economic health and fuel consumption. Moreover, the most critical concern of traffic congestion is a delay of emergency vehicles like ambulance and police vehicles, and firefighting trucks leading to an increase the human death and loss their essential things. In addition, this paper focuses to reduce the traffic congestion and traveling time of emergency vehicles. To overcome traffic congestion issues, an Optimal Intelligent Vehicle Control System for the emergency vehicle by intelligent traffic clearance (OIVC-VLC-VANET) is proposed. Firstly an improved whale optimization (IWO) algorithm is submitted for grouping the vehicle nodes based on their behaviors. Secondly, the differential search algorithm is used to select the next forwarding node using multiple constraints received from vehicles. Thirdly, the dragonfly algorithm is submitted for avoiding extra time due to the control packets exchange process. The results show that the proposed OIVC-VLC-VANET system can perform very efficiently in terms of quality constraints than existing systems.