Driven by the special requirements of the Lowpower 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.

No abstract

In RPL routing protocol, the DAO (Destination Advertisement Object) control messages are announced by the child nodes to their parents to build downward routes. A malicious insider node can exploit this feature to send fake DAOs to its parents periodically, triggering those parents, in turn, to forward the fake messages upward to the root node. In this study, we show how this behavior can have a detrimental side effect on the performance of the network, increasing power consumption, latency and reducing reliability. To address this problem, a new scheme is introduced to mitigate significantly the effect of the DAO attack on network performance.

We present a cloud-based healthcare system that integrates a formal care system (DACAR) with an informal care system (Microsoft HealthVault). The system provides high levels of security and privacy within a cloud environment, enabling sharing of both health records and the access rights, along the patient pathway. We also define a case study that can help in evaluating and in demonstrating the usefulness of a cloud-based integrated health care system.

In this paper, we introduce Drizzle, a new algorithm for maintaining routing information in the Low-power and Lossy Ne tworks (LLNs). The aim is to address the limitations of the curre ntly standardized routing maintenance (i.e. Trickle algorithm) in such networks. Unlike Trickle, Drizzle has an adaptive suppre ssion mechanism that assigns the nodes different transmission probabilities based on their transmission history so to boost the fairne ss in the network. In addition, Drizzle removes the listen-only pe riod presented in Trickle intervals leading to faster convergence time . Furthermore, a new scheme for setting the redundancy counter has be en introduced with the goal to mitigate the negative side effect of the short-listen problem presented when removing the listen-only pe riod and boost further the fairness in the network . The pe rformance of the proposed algorithm is validated through e xte nsive simulation e xperiments under different scenarios and ope ration conditions. In particular, Drizzle is compared to four routing maintenance algorithms in terms of control-plane overhead, powe r 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.