# Offloaded Computation for QoS Routing in Wireless Sensor Networks
## 1 Introduction  
In communication networks, Quality of Service (QoS) represents the essential requirements a network must fulfill to provide adequate service to its users. These requirements are articulated through specific conditions that must be satisfied for effective communication between a source and a destination [1]. It is important to acknowledge that QoS requirements can differ significantly among various applications, leading to distinct challenges within large-backbone networks and inter-domain and intra-domain contexts. Various comprehensive tools operating across different layers of the OSI protocol are available to support service providers in delivering QoS to users with particular needs. Traffic Engineering (TE) assumes responsibility for managing queues with designated priorities while employing diverse packet forwarding strategies, primarily at the Media Access Control (MAC) layer. QoS encompasses the performance, reliability, and availability levels that an application and its underlying infrastructure can deliver effectively. The objectives of QoS are integral to the decision-making processes associated with capacity allocation, loadbalancing, and admission control. A Service Level Agreement (SLA) is typically established between the service provider and the user to outline the expected services and their corresponding performance metrics. Additionally, the SLA specifies the methodologies for measuring performance and details the consequences of failing to meet the agreed-upon standards. Performance metrics are generally categorized into two primary classes: functional and non-functional metrics [2]. * Functional Metrics: These metrics define Key Performance Indicators (KPIs) that significantly impact user perceptions. Key examples include latency, energy efficiency, throughput, packet loss rate, and jitter. Each functional metric must be clearly defined for each service provided. * Non-Functional Metrics: These metrics assess service performance concerning deployment and management considerations. Notable examples include service availability, fault tolerance, service processing, and computational load. It is essential to highlight that QoS is classified as a functional metric, while performance, reliability, and availability are regarded as non-functional metrics. Wireless Sensor Networks (WSNs) are increasingly recognized for their effectiveness in collecting and communicating various data types across applications such as environmental monitoring, healthcare, and smart city development. In large-scale WSNs, data transmission to a sink node primarily utilizes a multi-hop routing mechanism, enabling data packets to be relayed through multiple intermediate nodes before reaching their final destination. These networks are designed to gather information that must be forwarded to applications requiring specific levels of QoS, including bandwidth, delay, jitter, and packet loss. Such information must be forwarded reliably to a sink node, base station, or border router (BR) for further processing. It is imperative to effectively address QoS requirements, often characterized by multiple constraints, through routing protocols specifically designed for WSNs, ensuring the reliability and optimal performance of the network. Recent studies, such as CERP [3], have investigated cooperative routing methods that improve both energy efficiency and QoS guarantees in WSNs. The primary objective of QoS in WSNs is to optimize network performance in alignment with user-defined requirements. Solutions often prioritize different types of traffic and allocate resources necessary to accommodate varying transmission needs, such as data, voice, and video. For instance, the IEEE 802.11e standard modifies the Media Access Control (MAC) layer by introducing different priority levels, known as access categories, which facilitate the effective categorization and scheduling of traffic. In a study by [PERSON] et al.