A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations <s> 2) Listen Interval Oriented Enhancements <s> RPL (IPv6 Routing Protocol for Low Power and Lossy networks) is a routing protocol recently standardized by the IETF. RPL has been designed to operate in energy-constrained networks with thousands of nodes, and therefore it is one of the most promising candidate routing protocols for Advanced Metering Infrastructure (AMI) networks. In this paper a performance evaluation of RPL is presented. An extensive study of the protocol is carried out with particular focus on Trickle, the algorithm adopted to control routing update distribution across the network. The performance of the protocol is analyzed considering different Trickle parameters in order to capture their impact on route formation and node power consumption. Results highlight that the nondeterministic nature of Trickle can lead to sub-optimal route formation especially when high message suppression is per-formed. In order to mitigate this issue, an enhanced version of the protocol, namely Trickle-F, is proposed in order to guarantee fair broadcast suppression. Trickle-F is demonstrated to be effective in obtaining more efficient routes with the same power consumption of the original version. <s> BIB001 </s> A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations <s> 2) Listen Interval Oriented Enhancements <s> The Trickle Algorithm has enjoyed much popularity and widespread use as a basic network primitive ensuring low-cost data consistency in lossy networks. Trickle is shaped by the so-called short-listen problem, hence the imposition of a listen-only period. Such a period allows Trickle to robustly address the short-listen problem at the expense of increased latency. In this letter, we introduce a simple yet powerful optimization to Trickle that can dramatically decrease Trickle's latency with virtually no additional overhead to its scalability and robustness. Extensive simulation and testbed experiments are reported here, yielding greater than a factor of 10 decrease in propagation time. <s> BIB002 </s> A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations <s> 2) Listen Interval Oriented Enhancements <s> Low-power wireless networks play an important role in the Internet of Things. Typically, these networks consist of a very large number of lossy and low-capacity devices, challenging the current state of the art in protocol design. In this context the Trickle algorithm plays an important role, serving as the basic mechanism for message dissemination in notable protocols such as RPL and MPL. While Trickle's broadcast suppression mechanism has been proven to be efficient, recent work has shown that it is intrinsically unfair in terms of load distribution and that its performance relies strongly on network topology. This can lead to increased end-to-end delays (MPL), or creation of sub-optimal routes (RPL). Furthermore, as highlighted in this work, there is no clear consensus within the research community about what the proper parameter settings of the suppression mechanism should be. We propose an extension to the Trickle algorithm, called adaptive-k, which allows nodes to individually adapt their suppression mechanism to local node density. Supported by analysis and a case study with RPL, we show that this extension allows for an easier configuration of Trickle, making it more robust to network topology. <s> BIB003 </s> A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations <s> 2) Listen Interval Oriented Enhancements <s> Wireless sensor network protocols very often use the Trickle algorithm to govern information dissemination. For example, the widely used IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) uses Trickle to emit control packets. We derive an analytical model of Trickle to take into account multiple redundancy constants and the common lack of synchronization among nodes. Moreover, we demonstrate message count unfairness when Trickle uses a unique global redundancy constant because nodes with less neighbors transmit more often. Consequently, we propose a heuristic algorithm that calculates a redundancy constant for each node as a function of its number of neighbors. Our calculated redundancy constants reduce unfairness among nodes by distributing more equally the number of transmitted messages in the network. Our analytical model is validated by emulations of constrained devices running the Contiki Operating System and its IPv6 networking stack. Furthermore, results very well corroborate the heuristic algorithm improvements. <s> BIB004
In BIB002 , the authors highlighted the problem of increased latency resulting from introducing the listen-only period in the Trickle algorithm. To address this problem, an Optimized-Trickle, (Opt-Trickle) is proposed. The authors observe that nodes receiving inconsistent transmissions simultaneously will reset their timers (returning to Imin) immediately, thus exhibiting a form of implicit synchronization. Such a synchronization in fact eliminates the need for the fixed listen-only period in the first interval and allows the affected nodes to pick a random time, t, from the range [0, Imin] . This is the only modification in OptTrickle. Summary and Insights: Although Trickle-F BIB001 has succeeded to some extent in solving the sub-optimality of constructed routes; the algorithm still suffers from slow convergence time due to the listen-only period. The study pertaining to Opt-Trickle BIB002 assumes a MAC protocol with 100% duty-cycle, which is neither reasonable nor realistic. Furthermore, Opt-Trickle still has a listen-only period in subsequent intervals, which would contribute to the increased latency especially in a lossy network where it is not guaranteed that a transmitted multicast message will reach all of its destinations at its first transmission in the first interval. In BIB003 , it is unclear why the study resorts to the number of messages received at specific node and not the number of actual neighbors, to estimate indirectly the network density at that node. Although this method might give an approximately accurate estimation for node degree when the network is characterized by synchronized intervals among its nodes, it may suffer from inaccurate estimation in non-synchronized networks. For instance, in a nonsynchronized network, the frequency of transmission may differ significantly from a node currently in its minimal interval to another node currently in its maximum interval. The node in its minimum interval will transmit more frequently, giving the receiver node an impression that it has more neighbors than it does actually has, thus affecting the accuracy of the network density estimation. The work in BIB004 did not demonstrate the impact of the proposed enhancement either on the quality of constructed routes nor on network power consumption. In addition, introducing two new parameters, the step and the offset, adds complexity, which is best avoided.