Packet Rate Reduction Research Articles

Improved Congestion Control in Wireless Sensor Networks Using Clustering with Metaheuristic Approach

The wireless sensor network (WSN) assists an extensive range of sensor nodes and enables several real-time uses. Congestion on the WSN is based on high pocket traffic and low wireless communication capabilities under network topology. Highly loaded nodes will consume power quickly and increase the risk of the network going offline or breaking. Additionally, loss of packet and buffer overflows would result in an outcome of increased end-to-end delay, performance deterioration of heavily loaded nodes, and transport communication loss. In this paper, a novel congestion control system is proposed to diminish the congestion on network and to enhance the throughput of the network. Initially, cluster head (CH) selection is achieved by exhausting K-means clustering algorithm. After the selection of cluster head, an efficient approach for congestion management is designed to select adaptive path by using Adaptive packet rate reduction (APTR) algorithm. Finally, Ant colony optimization (ACO) is utilized for enhancement of wireless sensor network throughput. The objective function increases the wireless sensor network throughput by decreasing the congestion on network. The proposed system is simulated with (Network Simulator NS-2). The proposed K-means C-ACO-ICC-WSN attains higher throughput 99.56%, 95.62% and 93.33%, lower delay 4.16%, 2.12% and 3.11% and minimum congestion level 1.19%, 2.33% and 5.16% and the proposed method is likened with the existing systems as Fuzzy-enabled congestion control through cross layer protocol exploiting OABC on WSN (FC-OABC-CC-WSN), Optimized fuzzy clustering at wireless sensor networks with improved squirrel search algorithm (FLC-ISSA-CC-WSN) and novel energy-aware clustering process through lion pride optimizer (LPO) and fuzzy logic on wireless sensor networks (EAC-LPO-CC-WSN), respectively. Finally, the simulation consequences demonstrate that proposed system may be capable of minimizing that congestion level and improving the throughput of the network.

Congestion Detection and Alleviation Mechanism Using a Multi-Level Cluster Based Cuckoo Hosted Rider Search Multi-Hop Hierarchical Routing Protocol in Wireless Sensor Networks

Wireless sensor networks congestion occurs easily due to its centralized traffic pattern. Normally, mono-sync wireless sensor network experiences multiple traffic flow congestion in the dense environment of the network, which leads to excess energy consumption and severe packet loss. To overcome these issues, a congestion detection and alleviation mechanism using cluster based heuristic optimized hierarchical routing protocol is proposed in this paper. Here, congestion detection and alleviation utilize the features of sensor nodes. The congestion is categorized into two types: (i) node level congestion and (ii) link level congestion. The node level congestion is detected by assessing the buffer utilization and the interval amid the consecutive data packets. The link level congestion is considered with computing link usage utilizing back-off step of round robin carrier sense multi-access with collision avoidance. Congestion detection and alleviation reactively affected node/link through cuckoo hosted rider search multi-hop routing algorithm. It has two phases: the cluster head selection and multi-path routing. Cluster head selection is performed through Taylor multiple random forest kernel fuzzy C-means clustering algorithm and multi-path routing is performed through cuckoo hosted rider search multi-hop routing algorithm. The simulation of the proposed method is done in network simulator tool. Here, the performance metrics, like packet delivery ratio, delay, energy consumption, packet drop, overhead, network lifetime and throughput are calculated. The experimental outcomes of the proposed technique shows 11.6%, 18.4% and 28.1% lower delay, 78.2%, 65.4% and 52.6% higher packet delivery ratio, and 29.2%, 37.4% and 40.8% lower packet drop compared with the existing methods, like congestion detection and alleviation using multi-attribute decision-making in optimization-based hybrid congestion alleviation routing protocol in wireless sensor networks, congestion detection and alleviation using hybrid K-means with greedy best first search algorithms in packet rate reduction utilizing adaptive weight firefly algorithm ant colony optimization based routing protocol in wireless sensor networks and congestion detection and alleviation using multi-input time on task optimization algorithm for altered gravitational search algorithm routing protocol in wireless sensor networks.

Energy Prediction for Teleoperation Systems That Combine the Time Domain Passivity Approach with Perceptual Deadband-Based Haptic Data Reduction.

We study the combination of the perceptual deadband (PD)-based haptic packet rate reduction scheme with the time domain passivity approach (TDPA) for time-delayed teleoperation and propose a novel energy prediction (EP) scheme that deals with the conservative behavior of the resulting controller. The PD approach leads to irregular packet transmission, resulting in degraded system transparency and reduced teleoperation quality when the PD approach is combined with the TDPA. The proposed method (PD+TDPA+EP) adaptively predicts the system energy during communication interruptions and allows for larger energy output. This achieves less conservative control and improves the teleoperation quality. Evaluation of the displayed impedance shows that the PD+TDPA+EP method achieves improved system transparency, both objectively and subjectively, when compared with related approaches from literature. According to a subjective user study, the PD+TDPA+EP method allows for a high packet rate reduction (up to 80 percent) without noticeably distorting the perceived interaction quality. We also show that the PD+TDPA+EP method is preferred over related approaches from literature in a direct comparison test. Thus, with the proposed PD+TDPA+EP method, a high data reduction and a high teleoperation quality are simultaneously achieved for time-delayed teleoperation.

Perception-Based Traffic Control for Shared Haptic Virtual Environments

Shared Haptic Virtual Environments (SHVEs) are often realized using a client–server communication architecture. In this case, a centralized physics engine, running on the server, is used to simulate the object-states in the virtual environment (VE). At the clients, a copy of the VE is maintained and used to render the interaction forces locally, which are then displayed to the human through a haptic device. While this architecture ensures stability in the coupling between the haptic device and the virtual environment, it necessitates a high number of object-state update packets transmitted from the server to the clients to achieve satisfactory force feedback quality. In this paper, we propose a perception-based traffic control scheme to reduce the number of object-state update packets by allowing a variable but not perceivable object-state error at the client. To find a balance between packet rate reduction and force rendering fidelity, our approach uses different error thresholds for the visual and haptic modality, where the haptic thresholds are determined by psychophysical experiments in this paper. Force feedback quality is evaluated with subjective tests for a variety of different traffic control parameter settings. The results show that the proposed scheme reduces the packet rate by up to 97%, compared to communication approaches that work without data reduction. At the same time, the proposed scheme does not degrade the haptic feedback quality significantly. Finally, it outperforms well-known dead reckoning, commonly used in visual-only distributed applications.

AVP: A Highly Efficient Transport Protocol for Low Bit Rate Multimedia Communications

Utilization of Internet communications in distance learning, distributed simulation, and distributed work groups involves multimedia transmission of animation, voice and video clips. Highly compressed audio-video data protocols are required for efficient Internet multimedia communications. Addressing this requirement, a new transport protocol called Audio-Video Protocol (AVP) for highly efficient multimedia communications on the Internet is presented. While providing similar real-time delivery functions as Real-Time Transport Protocol (RTP) and Real-Time Control Protocol (RTCP), AVP adopts a novel audio-based synchronization scheme. This synchronization scheme has two advantages. One is the overhead reduction through eliminating the timestamp in each transmitted data packet. The other is the packet rate reduction by putting multiple audio frames or mixed audio-video frames in a single AVP packet. As a result, the end-to-end media unit delay is reduced while achieving implicit synchronization. Furthermore, AVP provides adaptive quality of service (QoS) by the prioritized packetization scheme. Simulation results are presented to verify the advantages of the AVP protocol.

NETWORK TRAFFIC REDUCTION IN HAPTIC TELEPRESENCE SYSTEMS BY DEADBAND CONTROL

Current haptic (force feedback) telepresence systems operated over a communication network as, e.g. the Internet, require high packet rates for the transmission of the command and sensor signals. A novel approach to reduce the network traffic by means of deadband control is proposed. Data packets are only sent if the sampled signal changes more than a given threshold value. Passivity based reconstruction methods are introduced to reconstruct the untransmitted values at the receiver guaranteeing stability of the overall system. Experiments show that a packet rate reduction of up to 87% is achieved without impairing transparency.