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Data Analysis and Prediction for WSN Based on Linear and Quadratic Optimization Techniques
Published in Santosh Kumar Das, Massimiliano Giacalone, Fuzzy Optimization Techniques in the Areas of Science and Management, 2023
Manoj Kumar Mandal, Arun Prasad Burnwal, B. K. Mahatha, Abhishek Kumar
The wireless sensor network (WSN) is made up of sensor nodes and base stations (BS). The sensor nodes’ role is to detect environmental information and transmit it to the BS. This information is processed by the BS, which predicts the user inquiry and responds appropriately [1-2]. The WSN's key parameter is energy, which efficiently reflects on other parameters. Because each sensor node has a limited battery capacity, this low energy capacity is insufficient for each user's activity. Some work is based on the different challenges of management systems for security issues of the information system within the context of the wireless network. Some of the operation is based on coverage optimization and metaheuristic optimization that helps model several applications [3-4]. During the operation, sometimes nodes fail to transmit the data packet, or the path between nodes fails due to a lack of required energy. This issue affects other network parameters efficiently, like increase in some network metrics, such as packet delivery ratio, throughput, and goodput, and decreases in some network metrics, such as packet loss, overhead, and end-to-end delay. The combining variation of both types of network parameters degrades the network lifetime and affects the overall operation of the network.
Mobile Medium Access Control Protocols for Wireless Sensor Networks
Published in Shafiullah Khan, Al-Sakib Khan Pathan, Nabil Ali Alrajeh, Wireless Sensor Networks, 2016
Bilal Muhammad Khan, Falah H. Ali
Goodput is the total number of bits received correctly at the destination without retransmissions and control signals. Figure 5.7 shows the comparison of the goodput of the proposed protocol and CSMA/CA in mobile application. The result shows significant degradation of goodput in case of CSMA/CA. There are several factors behind the degradation of the goodput for the CSMA/CA. From Section 5.6.4, it is clear that the channel utilization is very poor and the latency in terms of setup time is very high. The other influencing factor is the presence of random backoff and problem of collision. As the number of nodes in the network increases, it also increases the number of potential contending nodes, which causes higher collision, more random backoff, and more retransmission of data. Hence, more and more packets are collided and the overall QoS falls drastically. It can be seen that at lower value of (BE), the goodput of the network is decreased. This is due to the fact that more number of nodes will be ready to transmit the data with lower backoff delay causing considerable rise in collision and thus contributing to lower goodput results. In case of MA-CSMA/CA, collision is minimized by allocating GTS for the mobile node entering the new cluster. Moreover, the average setup time for the proposed protocol is very low and the channel utilization is also on the high side. Hence, the goodput of the proposed scheme increases not only under increase number of active nodes but also on variable data traffic.
Wireless sensor and actuator network: Self-healing and ad-hoc routing protocol with load balancing
Published in Shin-ya Nishizaki, Masayuki Numao, Jaime Caro, Merlin Teodosia Suarez, Theory and Practice of Computation, 2019
R.K. Medel, L.A. Payofelin, P.G. Tee, J.E. Valle, F.K. Flores
Eq. (2), (3), (4) and (5) shows the formula for latency, throughput, goodput, and packet loss rate, respectively. Latency is calculated by the time the data packet was sent from the time the packet took to arrive at the destination. Throughput is obtained by dividing the product of the number of packets received, the size of packet, and 8 bits, with 60 seconds. Goodput is computed by dividing the product of the number of packets received, the payload size, and 8 bits, with 60 seconds. Packet loss rate is calculated by subtracting the number of packets not received from the number of packets sent, and multiplied by 100 percent. Test results are shown in Table 2.
A metric for measuring power efficiency and data throughput in mobile ad hoc networks
Published in International Journal of Parallel, Emergent and Distributed Systems, 2019
Todd A. Newton, Eugene B. John
One of the key performance metrics for characterizing a network is the end-to-end throughput it is able to provide for its nodes. However, it must be understood that not every bit that is transmitted is actually representing data. Different layers of protocols contain various amounts of overhead bits that aid in the delivery of the data payload but do not represent data itself. Some whole packets may entirely consist of overhead bits if they do not contain any data bits. Thus, in the context of determining throughput efficiency in a network, the term ‘throughput’ is more accurately thought of as ‘goodput’, or the sensor node’s application layer data bits transferred over a period of time.
Heuristic-based opportunistic network coding at potential relays in multi-hop wireless networks
Published in International Journal of Computers and Applications, 2023
The number of packets available for communication at any given instance also influences the performance of network coding. Goodput is considered as application-level network throughput, which excludes the protocol overheads of transport, network, and MAC layer. Thus, goodput takes into account only useful information transmitted between the communicating nodes. Hence, goodput gain as a parameter is considered to evaluate network performance. For the experimental analysis, the number of packets is considered as an offered load in network i.e. density of communication. Figure 9 presents the goodput gain of RHONC and COPE in terms of density of the communication.