rdlc data matrix

rdlc data matrix

rdlc data matrix

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rdlc data matrix

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13 8

50 % 40 %

avee[B 0 (A X ) ) . . a (Y , = (lq 01\np 0 Im)[vee(B) 0 dlag(vec A)].

Of additional interest, participants made nonoptimal responses only to a limited degree, thereby suggesting a compromise between the two.

clock in the system and the local clocks might not be synchronized So, we do not know the real execution order for these operations As an example, assume there are two copies of data item X, with each site storing one copy Let s suppose that T1 issues the W1(X) operation at Site 1 when the clock at Site 1 shows 10:00 Suppose T2 issues the W2(X) operation at Site 2 when the local clock at Site 2 indicates 10:02 The question is: Do we really know that W1(X) happened before W2(X) If the two clocks are synchronized, then obviously W1(X) starts before W2(X) in real time If the two clocks are not synchronized with a global clock, there is no way to know the order of these operations A commitment order of T1 T2 or T2 T1 may be the case.

sive, according to the development strategy used to carry out the projects. The standard classification is anticipative. Only if it becomes apparent, at some stage during the elaboration of the business case, that too little time exists to achieve the business objective under architecture, is the classification changed to offensive or defensive strategy. (In 7, Development with(out) Architecture, we will see what this actually means for the development route.)

Existing sensor network security research has been mostly on foundational cryptographic services, or applying cryptographic techniques to protect sensor network applications. Examples include resilient data aggregation [19 21], secure in-network processing [16], and hop-by-hop authentication for ltering out false data-injection attacks [17,18]. These are certainly critical issues for sensor network security. However, more issues are required for secure and resilient sensor networks. In particular, we need novel solutions to protect fundamental services such as location discovery and clock synchronization, which are also resilient in the presence of failures and malicious attacks. Moreover, intrusion detection in sensor networks is particularly important due to the fact that unattended sensor nodes can be easily captured and compromised. Since the ultimate goal of sensor networks is to collect data from physical environments, secure data collection and management is another critical issue as well. To illustrate the need for additional research, in the rest of this section we discuss attacks against location discovery in sensor networks. 5.4.1 Attacks Against Location Discovery

As a direct result of this, we cannot rely on global ordering of operations across sites for global serializability We have to devise a mechanism by which we can de nitely determine if a global schedule is serializable Fortunately, the solution to the problem is not as dif cult as it sounds The point that we must keep in mind is that, from a global perspective, it is not that important to know the absolute order of scheduling for con icting operations from different transactions across sites Instead, it is more important to know the relative order of scheduling con icting operations across transactions within each site In order to arrive at the solution, we need to introduce a new notation that allows us to incorporate site information with the data items our transactions are using.

We use the notation Oi(X@j) to indicate that Ti performs operation O on data item X at Site j For example, R1(X@1), W2(X@1) indicates a part of the schedule where transaction T1 performs a read of X at Site 1 and then T2 performs a write on X at the same site Obviously, these two operations are con icting and both are happening at Site 1 The local concurrency control at Site 1 will detect this con ict and will require T1 T2 at this site In this notation, data item X@1 is not considered the same data item as X@2 In fact, X@1 and X@2 are two different copies of X and are stored at two different sites Applying this concept to distributed systems, the global schedule W2(X@1), W3(X@1), W3(X@2), W2(X@2) contains two local con icts.

Another signaling breakdown is:

= 1)