A Survey on Trickle Algorithm: Comparative Analysis

Internet of Things (IoT) is an emerging area in the field of wireless communication. Due to its resource constraint environment, IETF gave a standard for IVP6 routing protocol for low power and lossy networks (RPL). The major component of RPL is Trickle algorithm. It is used to control the number of messages exchanged between devices and helps in early network stabilization. Due to its importance, it is crucial for researchers to understand this protocol. The absence of surveys in Trickle Algorithm motivates us to write this paper. In this paper, we compared different Trickle Algorithms based on performance parameters like convergence time, energy consumption, packet delivery ratio and others. Concluding, we can say that it is open research area in the designing parameters of Trickle�s Algorithms and we believe that this survey will be beneficial for researchers in their relevant work

History-based consistency algorithm for the trickle-timer with low-power and lossy networks

Recently, the internet of things (IoT) has become an important concept which has changed the vision of the Internet with the appearance of IPv6 over low power and lossy networks (6LoWPAN). However, these 6LoWPANs have many drawbacks because of the use of many devices with limited resources; therefore, suitable protocols such as the Routing Protocol for low power and lossy networks (RPL) were developed, and one of RPL's main components is the trickle timer algorithm, used to control and maintain the routing traffic frequency caused by a set of control messages. However, the trickle timer suffered from the short-listen problem which was handled by adding the listen-only period mechanism. This addition increased the delay in propagating transmissions and resolving the inconsistency in the network. However, to solve this problem we proposed the history based consistency algorithm (HBC), which eliminates the listen-only period based on the consistency period of the network. The proposed algorithm showed very good results. We measured the performance of HBC trickle in terms of convergence time; which was mainly affected, the power consumption and the packet delivery ratio (PDR). We made a comparison between the original trickle timer, the E-Trickle, the optimized trickle and our HBC trickle algorithm. The PDR and the power consumption showed in some cases better results under the HBC trickle compared to other trickle timers and in other cases the results were very close to the original trickle indicating the efficiency of the proposed trickle in choosing optimal routes when sending messages

A Novel Adaptive and Efficient Routing Update Scheme for Low-Power Lossy Networks in IoT

In this paper, we introduce Drizzle, a new algorithm for maintaining routing information in the Low-power and Lossy Networks (LLNs). The aim is to address the limitations of the currently standardized routing maintenance (i.e. Trickle algorithm) in such networks. Unlike Trickle, Drizzle has an adaptive suppression mechanism that assigns the nodes different transmission probabilities based on their transmission history so to boost the fairness in the network. In addition, Drizzle removes the listen-only period presented in Trickle intervals leading to faster convergence time. Furthermore, a new scheme for setting the redundancy counter has been introduced with the goal to mitigate the negative side effect of the short-listen problem presented when removing the listen-only period and boost further the fairness in the network. The performance of the proposed algorithm is validated through extensive simulation experiments under different scenarios and operation conditions. In particular, Drizzle is compared to four routing maintenance algorithms in terms of control-plane overhead, power consumption, convergence time and packet delivery ratio (PDR) under uniform and random distributions and with lossless and lossy links. The results indicated that Drizzle reduces the control-plane overhead, power consumption and the convergence time by up to 76%, 20% and 34% respectively while maintaining approximately the same PDR rates

Pervasive service discovery in low-power and lossy networks

Pervasive Service Discovery (SD) in Low-power and Lossy Networks (LLNs) is expected to play a major role in realising the Internet of Things (IoT) vision. Such a vision aims to expand the current Internet to interconnect billions of miniature smart objects that sense and act on our surroundings in a way that will revolutionise the future. The pervasiveness and heterogeneity of such low-power devices requires robust, automatic, interoperable and scalable deployment and operability solutions. At the same time, the limitations of such constrained devices impose strict challenges regarding complexity, energy consumption, time-efficiency and mobility. This research contributes new lightweight solutions to facilitate automatic deployment and operability of LLNs. It mainly tackles the aforementioned challenges through the proposition of novel component-based, automatic and efficient SD solutions that ensure extensibility and adaptability to various LLN environments. Building upon such architecture, a first fully-distributed, hybrid pushpull SD solution dubbed EADP (Extensible Adaptable Discovery Protocol) is proposed based on the well-known Trickle algorithm. Motivated by EADPs’ achievements, new methods to optimise Trickle are introduced. Such methods allow Trickle to encompass a wide range of algorithms and extend its usage to new application domains. One of the new applications is concretized in the TrickleSD protocol aiming to build automatic, reliable, scalable, and time-efficient SD. To optimise the energy efficiency of TrickleSD, two mechanisms improving broadcast communication in LLNs are proposed. Finally, interoperable standards-based SD in the IoT is demonstrated, and methods combining zero-configuration operations with infrastructure-based solutions are proposed. Experimental evaluations of the above contributions reveal that it is possible to achieve automatic, cost-effective, time-efficient, lightweight, and interoperable SD in LLNs. These achievements open novel perspectives for zero-configuration capabilities in the IoT and promise to bring the ‘things’ to all people everywhere

A directional preference ETX measure for the collection tree protocol in mobile sensor networks

There has been a growing interest in Wireless Sensor Networks (WSN) that utilizes mobile nodes for various purposes. These mobile wireless sensor networks tend to suffer from constant link breakages mainly caused by connected nodes moving apart, often moving very quickly. These lost connections require WSNs to constantly repair the network connections; this constant maintenance in turn causes power and packet losses and very noisy network conditions. However a performance extending metric can be implemented in order to reduce the frequency and occurrence of lost links between a parent node and its child. As such a directional preference Estimated Transmissions Count (ETX) measure was developed for the Collection Tree Protocol (CTP) in order to create longer lasting links. This thesis describes and measures the performance of this directional preference ETX measure utilizing various metrics such as Packet Reception Ratio, average number of beacon transmissions per node, Parent changes and various others. The Packet Reception Ratio metric is primarily used to compare this directional preference ETX measure to other popular WSN algorithms such as M-Leach, Geographic Greedy Forwarding and as well regular CTP due to the differences in topology between these algorithms. Based on the packet reception ratio the directional preference ETX measure improves the performance of CTP such that it is capable of outperforming M-Leach in various scenarios

A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations

Driven by the special requirements of the Low-power and Lossy Networks (LLNs), the IPv6 Routing Protocol for LLNs (RPL) was standardized by the IETF some six years ago to tackle the routing issue in such networks. Since its introduction, however, numerous studies have pointed out that, in its current form, RPL suffers from issues that limit its efficiency and domain of applicability. Thus, several solutions have been proposed in the literature in an attempt to overcome these identified limitations. In this survey, we aim mainly to provide a comprehensive review of these research proposals assessing whether such proposals have succeeded in overcoming the standard reported limitations related to its core operations. Although some of RPL’s weaknesses have been addressed successfully, the study found that the proposed solutions remain deficient in overcoming several others. Hence, the study investigates where such proposals still fall short, the challenges and pitfalls to avoid, thus would help researchers formulate a clear foundation for the development of further successful extensions in future allowing the protocol to be applied more widely

Efficient Routing Primitives for Low-power and Lossy Networks in Internet of Things

At the heart of the Internet of Things (IoTs) are the Low-power and Lossy networks (LLNs), a collection of interconnected battery-operated and resource-constrained tiny devices that enable the realization of a wide range of applications in multiple domains. For an efficient operation, such networks require the design of efficient protocols especially at the network layer of their communication stack. In this regards, the Routing Protocol for LLNs (RPL) has been developed and standardised by the IETF to fulfil the routing requirements in such networks. Proven efficient in tackling some major issues, RPL is still far from being optimal in addressing several other routing gaps in the context of LLNs. For instance, the RPL standard lacks in a scalable routing mechanism in the applications that require bidirectional communication. In addition, its routing maintenance mechanism suffers from relatively slow convergence time, limiting the applicability of the protocol in time-critical applications, and a high risk of incorrect configurations of its parameters, risking the creation of sub-optimal routes. Furthermore, RPL lacks in a fair load-distribution mechanism which may harm both energy and reliability of its networks. Motivated by the above-mentioned issues, this thesis aimed at overcoming the RPL’s weaknesses by developing more efficient routing solutions, paving the way towards successful deployments and operations of the LLNs at different scales. Hence, to tackle the inefficiency of RPL’s routing maintenance operations, a new routing maintenance algorithm, namely, Drizzle, has been developed characterized by an adaptive, robust and configurable nature that boosts the applicability of RPL in several applications. To address the scalability problem, a new downward routing solution has been developed rendering RPL more efficient in large-scale networks. Finally, a load-balancing objective function for RPL has been proposed that enhances both the energy efficiency and reliability of LLNs. The efficiency of the proposed solutions has been validated through extensive simulation experiments under different scenarios and operation conditions demonstrating significant performance enhancements in terms of convergence time, scalability, reliability, and power consumption

Optimizing the trickle algorithm

The Trickle Algorithm has enjoyed much popularity and widespread as a basic network primitive ensuring low-cost data consistency in lossy networks. Trickle was shaped by the so called short-listen problem hence imposing a listen-only period. Such a period allows Trickle to robustly address the short-listen problem but 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 extra overhead to its robustness and scalability. Extensive simulation and testbed experiments are reported here with greater than a factor of 10 times decrease in propagation time