Data prioritization of heterogeneous data in wireless sensor networks gives meaning to mission-critical data that are time-sensitive as this may be a matter of life and death. However, the standard IEEE 802.15.4 does not consider the prioritization of data. Prioritization schemes proffered in the literature have not adequately addressed this issue as proposed schemes either uses a single or complex backoff algorithm to estimate backoff time-slots for prioritized data. Subsequently, the carrier sense multiple access with collision avoidance scheme exhibits an exponentially increasing range of backoff times. These approaches are not only inefficient but result in high latency and increased power consumption. In this article, the concept of class of service (CS) was adopted to prioritize heterogeneous data (realtime and non-real-time), resulting in an optimized prioritized backoff MAC scheme called Class of Service Traffic Priority-based Medium Access Control (CSTP-MAC). This scheme classifies data into high priority data (HPD) and low priority data (LPD) by computing backoff times with expressions peculiar to the data priority class. The improved scheme grants nodes the opportunity to access the shared medium in a timely and power-efficient manner. Benchmarked against contemporary schemes, CSTP-MAC attained a 99% packet delivery ratio with improved power saving capability, which translates to a longer operational lifetime.

Routing Protocol for Low-power and Lossy Network (RPL) with IPv6 support is the de facto standard for routing over Low-power and Lossy Network (LLN) called Wireless Sensor Networks (WSN). Objective Functions namely Minimum Rank with Hysteresis Objective Function (MRHOF) and Objective Function Zero (OF0) together with the Internet Control Messaging Protocol (ICMP) control messages, propel RPL to constructs routing paths called Destination Oriented Directed Acyclic Graph (DODAG), for packet routing within the sensor network. To the best knowledge of the authors, no detailed investigation has been carried out to unravel the dynamics of how these control messages impact on the network with respect to DODAG formation right before convergence is attained, particularly from the perspective of MRHOF and OF0. In this paper, the authors investigated the various types of control messages (DODAG Information Solicitation, DODAG Information Object and Destination Advertisement Object) used to setup the DODAG. RPL Simulations was carried out on one 100 nodes, starting with 10 nodes and incremented by 10 until the 100th node. Each simulation was repeated five times with a confidence level of 95%, which statistically signifies a reliable and acceptable confidence interval, for a duration of thirty minutes. Results obtained showed that the DIS–OF0 generated the least packets with 125 packets, followed by DAO–MRHOF with 1357 packets and the most generated; DIO–MRHOF with 1536 packets. Subsequently, MRHOF had higher Convergence Time of 130.67 seconds as to 87.93 seconds for OF0. This information is valuable for both the academia and industry.

Wireless Sensor Networks (WSN) is the network of the resource-constrained network which forms the foundation of the Internet of Things (IoT). The Routing Protocol for Low-power and Lossy Networks (RPL) is responsible for generating and managing data routing paths. Nodes implementing RPL uses the mechanics of Objective Function (OF) to select the preferred next-hop node – parent node, and optimal routing path to the destination node. If routing decisions are not efficiently made, this results in increased collision domain, leading to packet losses and packet retransmission which impairs the network operational lifetime. In this study, we present the Contiki Operating System (OS), a state-of-the-art OS for IoTs, ContikiRPL; Contiki variant of RPL. We investigated the performance of RPL with respect to its two OFs; Objective Function Zero (OF0) and the Minimum Rank with Hysteresis Objective Function (MRHOF). The performance of these OFs was evaluated on the following metrics; Packet Delivery Ratio (PDR), Power consumption, and network latency. The result shows that MRHOF outperformed OF0 on all metrics with an overall average PDR of 91.5%, a latency of 44ms, and power consumption of 1.72mW across all nodes. This results in optimal network performance with improved network operational lifetime.

The quest for faster and seamless mobile communication services has given rise to the Fifth Generation (5G) mobile communication technology. 5G presents enormous opportunities for end-users, businesses, and the global economy at large. The major edge 5G has over its predecessor technologies; the 3rd and 4th Generation (3G and 4G), is ultra-low latency, which translates to ultra-fast data speed, which has the potential to peak to about 1Gbps at the frequency range of 6GHz to 100GHz. Its application of Multiple Input, Multiple Output (MIMO) antenna technology enables it to beam dedicated radio signals to 5G enabled User Equipment (UEs) using the advanced beam steering algorithm. This results in maximum data throughput with ultra-high bandwidth transmission to end-user applications resulting in new and never-seen-before business opportunities across different industries, investments, and business services. By expanding the scope of wireless technologies and making devices more autonomous, 5G has the potential to reduce carbon emission footprint and encourage greener communities. The application of 5G cuts across all spheres of our lives; industry, transportation, education, communications, health, and businesses. 5G is more inclusive, progressive, proven, and powerful than any of its predecessor generations of communications technology. With more power and improved efficiency, 5G is on its way to creating a truly connected world.