The advent of Internet of Things (IoT) brought innovation along with unprecedented benefits of convenience and efficacy in many operations that were otherwise very cumbersome. This innovation explosion has surfaced a new dimension of vulnerability and physical threat to the data integrity of IoT networks. Implementing conventional cryptographic algorithms on IoT devices is not future-proof as these devices are constrained in terms of computational power, performance, and memory. In this paper, we are proposing a novel framework, a unique model that integrates IoT networks with a blockchain to address potential privacy and security threats for data integrity. Smart contracts are instrumental in this integration process and they are used to handle device authentication, authorization and access-control, and data management. We further share a new design model for interfaces to integrate both platforms while highlighting its performance results over the existing models. With the incorporation of off-chain data storage into the framework, overall scalability of the system can be increased. Finally, our research concludes how the proposed framework can be fused virtually into any existing IoT applications with minimal modifications.
A mobile ad hoc network (MANET) is a network consisting of a set of wireless mobile nodes that communicate with each other without centralized control or established infrastructure. The mobility model should represent the realistic behavior of each mobile node in the MANET. Routing protocols for ad hoc networks are typically evaluated using simulation, since the deployment of ad hoc networks is still relatively rare. However, past evaluations of multicast routing protocols have utilized a single, simple Random way point mobility model, and thus do not capture the variety of mobility patterns likely to be exhibited by ad hoc applications. In this paper, the results on the simulation study of the impact of different mobility models on Multicast Routing Protocols are presented. The performance of On Demand multicast Routing Protocol (ODMRP) and Adhoc demand Driven Multicast Routing(ADMR) protocol under different mobility scenario is evaluated. The results show that the throughput of ADMR is higher than of ODMRP at high mobility. This is achieved at the cost of increase in delay and transmission over head. Under low mobility, ODMRP has higher throughput than AMDR. Among the three mobility models considered, the throughput of ODMRP is the highest at low mobility. The results show that the protocols performances vary widely across the different mobility models.
In recent years, energy efficiency has become a major cause of concern in mobile networks. The overwhelming applications and services provided by the evolving fifth‐generation (5G) technologies consume a substantial amount of energy, especially at the user equipment (UE). The 3rd Generation Partnership Project has proposed discontinuous reception (DRX) as a power saving technique for the UE. The DRX protocol has been used by different generation mobile standards. In this paper, the performance of hybrid directional DRX (HD‐DRX) for 5G communication with beam searching is improved upon by augmenting intermediate single packet active states in the short and long sleep cycles for light traffic in 5G networks. The supplementary active states save power by allowing the UE to receive packets within the sleep periods up to a certain threshold without transitioning to the active state. The short bursts of packets in the light traffic are received directly through the intermediate active states without beam searching. Once the given threshold exceeds, the system functions as normal HD‐DRX for the heavy traffic without the intermediate states. The proposed model is analyzed as a semi‐Markov process with the bursty packet data traffic model. The numerical results of the proposed model show 3.1% improvement in power saving and reduction in average delay by around 2.5 s compared to the HD‐DRX. Further studies can help deep dive into operationalizing this on a mass scale.
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