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At first, our Eclipse/JUnit integration will be simple In keeping with the cucumber story, not only will we use JUnit as the functionality to be accessed, we will use JUnit itself to develop our plug-in Instead of the metacircular, self-referential style of the example in [1] Test-Driven Development: By Example, we will use the version of JUnit built into Eclipse In particular, we will use the extension of JUnit for testing plug-ins, PDE JUnit

The rest of the chapter is organized as follows. The challenges and design issues of time synchronization protocols in sensor networks are summarized in Section 17.2. In Section 17.3, we survey some of the time synchronization protocol including possible attacks and proposed countermeasures against these attacks. The types of attackers and attacks are presented in Section 17.4. Section 17.5 gives detailed discussion about the approaches for secure time synchronization. We conclude in Section 17.6.

Sufficient retirement income. What does this mean What sources of income should be used The universal three-legged stool of social security, private savings, and employer-sponsored plans comes to mind. See the ensuing box for more information about replacement income analysis. Employees. Is it employees or employees and spouses What about other demographic trends like same-sex marriages, second/third families, and elder care and long-term care needs

K Beck, Test-Driven Development: By Example Addison-Wesley, Boston, 2003 ,

17.2 TIME SYNCHRONIZATION IN SENSOR NETWORKS 17.2.1 Challenges Different applications will have different synchronization requirements, and almost all the synchronization methods rely on message exchange between nodes. The nondeterminism in the network operations can cause delays in the message delivery and, in turn, contributes to the error in synchronization. Let us see how the source of a message s latency is decomposed in Figure 17.2. According to references 5 and 6, the time synchronization schemes have four basic packet delay components: send time, access time, propogation time, and receive time. r Send Time. This is the time it takes to construct a message at the sender including the overhead of the operating system and the time to transfer the message to the network interface. r Access Time. This is the delay encountered at the medium access control (MAC) layer prior to accessing the transmission channel due to contention, collisions, and so on. This delay is dependent on the MAC protocol in place. For instance, carrier sensing multiple access (CSMA) [7] requires every node to sense the carrier before transmitting, and it does not start a transmission if the medium is busy. CSMA/CA consists of both carrier sensing and a collision avoidance; the IEEE 802.11 standard [8] is the best-known instance of CSMA/CA. r Propogation Time. This is the time required in propagation of the message from sender to the receiver. The propagation time varies, depending on the location of the sender and the receiver. For instance, if they are one-hop neighboring nodes in an ad hoc network, the propagation time equals to the physical propagation time

The first circle will take you through the development of the JUnit engine The second circle will add all the bits and pieces that go into making a complete Eclipse contribution The contributions add up to a new way to think about tests during the development process, and each bit shows you a useful corner of Eclipse

in node coverage in an area, an increase in packet latency, excessive energy consumption per packet delivery, an increased risk to important nodes such as the base station from an approaching target, and so on. A weighted average may also be pursued to combine multiple dependability metrics based on the application in hand. Once a node has the motive, it will consider moving to a new position. Such consideration does not necessarily lead to an actual relocation. The node would need to qualify the impact of repositioning at the new location on the network dependability. Therefore the when and where issues of the node movement are very closely interrelated. In addition, the node would have to assess the relocation overhead. Such overhead can be incurred by the node and the network. For example, if the base station or the sensor node is a robot, the energy consumed by the mechanical parts in the movement is a signi cant overhead to the lifetime of the robot s battery and thus should be minimized. Moreover, when energy and timeliness metrics are of utmost concern, the impact on the lifetime of individual sensors and on route maintenance has to be considered, respectively.