## 1 Introduction  
Autonomous self-aware and adaptive systems provide the means to solve the computational complexities of a dynamic environment. Autonomous self-aware routing algorithms possess the capability of configuring, healing, optimizing, and protecting themselves autonomously [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]. This also entails the ability to find the best means for optimizing performance in resource-constrained environments. Sensor networks are exposed to inhospitable environments and need to be adapted to changes in the environmental parameters or users. For example, a sensor network deployed to track and trace enemy positions in a battlefield must adapt to changes in the enemy position. In addition, a sensor network that helps the robot in a car manufacturing factory must provide the robot with extended situational awareness in its vicinity to adapt to the movement of the robot for better functioning of the system. Sensor networks that are resource constrained have low power, low communication, and minimal computational capabilities. In addition, they possess low storage capabilities, low cost, reliability and fault tolerance, which are the critical sensor network design considerations [1, 2, 3]. Sensor nodes may fail for various reasons. These include radio interference, battery failure, and synchronous and asynchronous communication mechanisms. These failures mainly arise as a result of software or hardware faults, malicious code, environmental changes, and timing closure. On the whole, the result of such an event is that a sensor node becomes inaccessible or disrupts certain operating conditions that are critical to providing the required service. Communication in sensor networks is highly critical because the links in a network are prone to faults and errors. For instance, the collision of network packets may result in a failure. The presence of such a failure in a routing protocol will lead to considerable network packet drops resulting in excessive network delays and consumption of a substantial amount of energy [10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]. This research was motivated mainly by the observation that the traditional fault-tolerant approach to routing in a wireless sensor network introduces more redundant transmission and retransmission of network packets and consumes an excessive amount of energy. In addition, they are also deficient in terms of their autonomous self-awareness and adaptive capabilities in routing packets from their sources to their destinations in the presence of transient and permanent node failures and in highly scalable and congested networks. The essential concerns here are how to avoid the problem of packet flooding because of broadcasting and network scalability issues. To address these issues, our approach attempts to reduce the number of redundant network packets caused by flooding. Both the SSR [40, 41, 51, 52] and SHR [24, 53] routing protocols make use of a prioritized back-off delay for forwarding packets, with only the receiver of the forwarding packets reaching the destination. Our approach focuses on the minimization of these control packet overheads and efficient end-to-end data delivery. In doing so, we combined both the continuous and slotted prioritized transmission back-off delays to obtain local and global network state information and a multiple randomize function for faster routing convergence and efficient and reliable route repair in the presence of transient and permanent node failures. In our proposed scheme, the sensor node that transmits the packets contains information pertaining to its neighbors in the control header packets. The sender node is self-aware and adaptive if it knows both local and global state information contained in the control packets.