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LLNs (Low Power and Lossy Networks) are becoming hot research topics due to challenges posed by their limited battery life, computing power, memory and transmission power. LLNs require a routing protocol which can perform efficiently with their limitations. IETF has come up with RPL as standard routing protocol for LLNs. It builds energy efficient network. But it also has major limitations and several research have happened to overcome the same. This paper is survey of RPL challenges and recent research on RPL extensions. Major RPL limitations include packet loss under noisy scenario, increased DODAG depth causing high energy consumption. TTA (Trickle Timer Algorithm) is important part of RPL. It is used to manage control messages flow. Limitation of trickle algorithm results in problem of short time for listening and it can make few nodes crave for delay and higher latency. E-Trickle is proposed to overcome the listen only period, improve convergence time and energy consumption. QOI (Quality of Information) aware RPL reduces the energy consumption with less data transmission. RPL operates under one sink. Entire data flows towards the single sink. RPL doesn’t specify when, where and how more number of sinks need to be used. Dynamic rescue sink is RPL enhancement built with real timetracking of nodes’ performance in RPL networks to propose new sinks when required. AMI (Advanced metering infrastructure) is one of the application in smart grid for connecting smart metering devices at homes. It is critical to have efficient routing protocol for AMI as the smart meter nodes are resource constrained. AMI with high density networks suffer from high packet loss, network congestion retransmissions, increased latency, control traffic overhead and power consumption. LQE (Link Quality Estimation) influences quality of selected route and energy consumption. RL-probe measures link quality precisely with small overhead and energy consumption. RL-probe reduces packet loss by reacting to link quality variations and link failures due to mobility. Communication overhead needs to be as minimal as possible inLLNs with limited resources. Adaptive timing model uses dynamic method to decide frequency of executing objective function to construct DODAG based on degree of surrounding changes and reduces the control messages overhead. Objective is to bring down the PLR (packet loss ratio), overhead of control messages and battery usage. RPL doesn’t give good results for high throughput and changes in network conditions. This prevents use of RPL in high speed sensors and mobile sensing applications. BRPL is extension to RPL which combines RPL objective function (OF) with back pressure routing to handle dynamic traffic load and mobility. |
