Finite state automata congestion control

The energy efficiency issue even gets more challenging in the sensor-enabled network because energy consumption is a critical key in the design of WSNs as sensors are small devices with power-constraint due to their limited battery capacity. However, a huge number of the request packets is generated in ICN due to its packet flooding strategy, which causes high traffic, then increases the congestion rate and network devices power consumption as analyzed in our previous work. Typically, in ICN, additional network components are added to perform the functions of data naming, and content caching by establishing data flows between content locations and content consumers for the goal of matching the desired content for user requests. Among various proposed FI architectures, Information-Centric Networking (ICN) is a promising design as it is usually realized through the overlay approach. Thanks to the simple deployment and various practical applications, wireless sensor networks (WSNs) have become a critical factor for the Future Internet (FI) paradigm in the IoT era with the rapidly growing number of Internet users. From the advantage of the Internet architecture, Internet of Things (IoT) has been developed in which different types of devices or objects things can make decisions, communicate, and exchange data with each other. Nowadays, communication represents one of the most important parts of our interconnected world because the Internet is a fundamental technology that provides many beneficial applications for our society and daily lives. The evaluation results using ndnSIM (a widely-used ICN simulator) show that the proposed model can provide higher network performance efficiency with lower energy consumption for the future Internet by achieving higher throughput with higher cache hit rate and lower Interest packet drop rate as we increase the number of IoT sensors in ICN. We also design the sensor power-based cache management strategy, and an adaptive Markov-based sensor scheduling policy with selective sensing algorithm to further maximize power savings for the sensors. The proposed network system uses the chunk-by-chunk aggregated packets according to the content popularity to diminish the number of exchanged packets needed for data transmission.

In this paper, we propose a smart congestion control mechanism to diminish the network congestion rate, reduce sensor power consumptions, and enhance the network performance of ICN at the same time to realize a complete green and efficient ICN-based sensor networking model. Though ICN offers considerable benefits over the existing IP-based Internet architecture, its practical deployment in real life still has many challenges, especially in the case of high congestion and limited power in a sensor enabled-network for the Internet of Things (IoT) era. It can't accept any string which ends with 1, because it will never go to the final state q1 on 1 input, so the string ending with 1, will not be accepted or will be rejected.Information-Centric Networking (ICN) is a new Internet architecture design, which is considered as the global-scale Future Internet (FI) paradigm. It can accept any string which ends with 0 like 00, 10, 110, 100.etc. In the above diagram, we can see that on given 0 as input to DFA in state q0, the DFA changes state to q1.

Finite state automata congestion control