A Survey on Investigating the Need for Intelligent Power-Aware Load Balanced Routing Protocols for Handling Critical Links in MANETs <s> QoS Requirements and Challenges <s> This paper describes a systematic approach to building micro-solar power subsystems for wireless sensor network nodes. Our approach composes models of the basic pieces - solar panels, regulators, energy storage elements, and application loads - to appropriately select and size the components. We demonstrate our approach in the context of a microclimate monitoring project through the design of the node, micro-solar subsystem, and network, which is deployed in a challenging, deep forest setting. We evaluate our deployment by analyzing the effects of the range of solar profiles experienced across the network. <s> BIB001 </s> A Survey on Investigating the Need for Intelligent Power-Aware Load Balanced Routing Protocols for Handling Critical Links in MANETs <s> QoS Requirements and Challenges <s> The adoption of wireless sensor networks by applications that require complex operations, ranging from health care to industrial monitoring, has brought forward a new challenge of fulfilling the quality of service (QoS) requirements of these applications. However, providing QoS support is a challenging issue due to highly resource constrained nature of sensor nodes, unreliable wireless links and harsh operation environments. In this paper, we focus on the QoS support at the MAC layer which forms the basis of communication stack and has the ability to tune key QoS-specific parameters, such as duty cycle of the sensor devices. We explore QoS challenges and perspectives for wireless sensor networks, survey the QoS mechanisms and classify the state of the art QoS-aware MAC protocols together with discussing their advantages and disadvantages. According to this survey, we observe that instead of providing deterministic QoS guarantees, majority of the protocols follow a service differentiation approach by classifying the data packets according to their type (or classes) and packets from different classes are treated according to their requirements by tuning the associated network parameters at the MAC layer. Design tradeoffs and open research issues are also investigated to point out the further possible research directions in the field of QoS provisioning in wireless sensor networks at the MAC layer. <s> BIB002
QoS is the ability of a network to satisfy user and/or application requirements. Guaranteeing a certain QoS is a challenging issue due to the unpredictable and unstable wireless topology and severe resource (energy) constraints BIB002 . There are two main types of QoS provisions: hard QoS and soft QoS. Hard QoS should be provided with deterministic QoS (i) Resource Constraints. Due to mobility and thereby frequent switching, MANETs lack of bandwidth, energy and processing capability. But these are adequate unlike those in wireless sensor networks (WSN), but that is a different issue. However, limited energy is the most crucial one since in many scenarios it is impossible or impractical to replace or recharge batteries of mobile nodes on the move, especially in public transportation in rural areas. Although energy harvesting via solar energy BIB001  seems to be a promising solution to energy scarcity, present solar panels are still too large for mobile devices. (ii) Node Deployment. Unlike WSNs, the deployment of mobile nodes has to beat random. Therefore, neighbor discovery, path discovery, geographical information of the nodes, and clustering are the issues to be solved. (iii) Topology Changes. Changes in network topology might be due to mobility of nodes, failures in wireless links, improper functioning of mobile nodes, and depletion of energy and related constraints. In addition, sleep-listen schedules employed by power management protocols for energy saving also cause frequent topology changes. Inevitably, dynamic nature of the MANET topology introduces an extra challenge for QoS support. (iv) Unbalanced Traffic. Due to mobility and induced dynamism, sometimes amobile node may have too many data to handle and at times it may be not. Since there is no central entity to obtain an overall picture of what is happening within the underlying network, irregular traffic creates inefficient resource utilization. Smart routing protocols share load across routes but at the cost of a substantial overhead.