# A Cross-Layer Optimization QoS Scheme in Wireless Multimedia Sensor Networks
## 1 Introduction  
Real-time applications, including multimedia applications, have been developed as important services in various types of networks [1; 2]. In wireless multimedia sensor networks, real-time and non-real-time applications coexist. In wireless multimedia sensor networks, there are two essential problems. Firstly, as real-time and non-real-time applications have different QoS requirements, it is valuable to design QoS schemes which provide DiffServ. Secondly, as wireless sensor networks are energy-constrained, it is desirable to prolong network lifetime and reduce energy consumption while satisfying the QoS demands of the applications. The mainstream approach of QoS schemes providing DiffServ is to maintain different data queues for different applications. Queues are assigned different transmission priorities according to the types of applications that the queues support. The existing QoS schemes providing DiffServ can be divided into four categories of algorithms: media access control schemes [3; 4], scheduling schemes [5; 6; 7; 8; 9; 10; 11], routing schemes [12; 13; 14], and cross-layer control schemes [15; 16; 17]. However, in these works, after initial allocation, the priorities of the queues cannot be re-adjusted according to the real-time end-to-end situation. In the case of a shortage of resources, services with low priorities might obtain hardly any transmission opportunities. In [18], a DQS (Differentiated Queueing Services) scheme was proposed in which packets of all services are buffered in the same data queue at each node. The queueing sequence of a packet in the queue is decided according to its remaining lifetime. This queue structure means that any packet can gain transmission opportunities according to its end-to-end delay requirement and end-to-end situation. In [19], a DQS scheme is applied to wireless mesh networks. In [20], a DQS-based queueing algorithm was proposed in which event QoS parametersare used to reflect the actual need of non-end-to-end applications in wireless sensor networks. However, in [18; 19; 20] link scheduling was not considered. Algorithms of energy consumption control consist of three categories: cluster-based schemes [21; 22; 23; 24; 25; 26; 27; 28], optimization-based schemes [29; 30; 31; 32; 33; 34; 35; 36; 37], and backpressure-based schemes [38; 39; 40; 41; 42; 43]. Cluster-based schemes can balance the energy consumption of nodes and prolong network lifetime through selecting cluster-head nodes and forming clusters according to some ingenious criteria. TDMA (Time Division Multiple Access) scheduling is mostly utilized in clusters. However, cluster-based schemes may result in low utilization of wireless resources when nodes are non-uniformly distributed. This may degrade QoS performances. In optimization-based schemes, network utility, network lifetime, or energy consumption are used as the optimization objective. Optimization-based QoS schemes are designed based on the process of solving optimization problems. Unlike optimization-based schemes, backpressure optimization problems are established based on a Lyapunov optimization framework with time being slotted, and the lower bounds of the time average values of optimization utilities achieved by backpressure-based schemes can be pushed arbitrarily to the optimal values [44]. In [38; 49; 40], bias factors relating to the residual energy of nodes or distances between nodes are introduced into link-weight calculation to control transmission scheduling. In [41] and [42], both data queues and energy queues are utilized in Lyapunov functions for cross-layer control. In [43], the shortest path is combined with a backpressure scheme in the process of next-hop node selecting to prolong network lifetime. However, two problems are ignored in existing optimization-based and backpressure-based schemes.