## 1 Introduction
For infrastructure based WSN, network entities like gateways, access points and network manager are required (Figure 2). Hence, a strict categorization for WSN deployment strategy is the structured and non-structured WSN [1]. Depending on the environment, WSNs can be classified into terrestrial WSN, underwater WSN, underground WSN,  
Figure 1: Network elements in CPS architecture. multi-media WSN and mobile WSN [2]. An unstructured WSN would consist of a dense collection of sensor nodes deployed in an _ad hoc_ unattended manner. The unstructured WSNs are difficult to manage in terms of detecting connectivity failures [6]. The structured WSN nodes are deployed in a pre-defined manner at strategic locations, e.g., in a linear or hierarchical topology. Applications of WSN range from military tracking, environment surveillance, natural disaster relief, biomedical health monitoring and seismic sensing to hazardous environment exploration. A major classification of WSN applications lies in tracking and environmental monitoring scenarios [7]. Unlike traditional wireless networks and more intelligent radios that are capable of adopting communication parameters in run time, WSNs come with their own resource and design constraints [8, 9]. Resource constraints include limited bandwidth, limited amount of energy, limited processing power, low storage capacity, and short communication range. Such constraints are in general not coupled with other wireless and cellular networks [10, 11]; hence WSN require special deployment consideration from coverage perspective as well. Design constraints vary according to the application of WSN and the type of environment. Research in WSNs aims to meet these constraints by introducing new design concepts, improving existing protocols, developing new algorithms and testing applications in different scenarios. From a network management perspective and in terms of application requirements, it is important that the sensor nodes are capable of self-organization, _i.e._, able to manage and control their actions in the network and their resource utilization. WSN standards that have been developed and widely adopted define the necessary protocols, functions and  
Figure 2: A typical wireless sensor network setup with central monitoring. algorithms for sensor node interfaces to work without obstruction within the network realm. Some of the notable WSN standards include IEEE 82.15.4, ZigBee, WirelessHART, ISA100.11, IETF 6 LowPAN, IEEE 802.15.3 and Wibree [1,7] (Table 1). The possibility to develop a CPS enabled sensor network has arisen through the accelerated development of wireless technology and embedded computing with applications like micro sensing MEMS, inertial motion detection, bio-signal sensing, environment parameter sensing, location and vehicular movement detection [12]. While a single platform is being sought for defining common parameters, the major technical differences need to be emphasized. WSN has been designed and implemented mainly with the idea of communicating sensing related data with coordination over some limited geographical environment. CPS, on the other hand, utilizes a broader definition and dimension of sensing data over multiple networks (multiple WSNs) with a Cloud specific link to the Internet with the aim of providing flexible control and intelligence. Major technical requirements for CPS and WSN have been summarized in Table 2. CPSNs may encompass several WSNs; hence, the CPSN layer is technically able to support dynamic network formations, cross layer communications, larger geographic area coverage with looped actuation, mobility patterns and use of knowledge mining algorithms. The CPS architecture resembles traditional embedded systems that aim to integrate abstract computations with physical processes. Contrary to traditional embedded systems, CPS provides an interconnected interaction with outputs and inputs that pertain to physical existence and are standalone devices (Figure 3). The main layers of CPS are the virtual layer and physical layer.