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We illustrate the technique for detecting locally stable predicates for deadlocks A deadlock in a distributed system can he characterized using the wait-for graph (WFG): a graph with nodes as processes and an edge from Pi to 1%if P, is waiting for Pj for a resource to finish its job or transaction Thus, an edge from to means that, there exist one or more resources held by Pj without which cannot, proceed We have assumed that, it process needs all the resources for which it, is waiting to finish its job Clearly, if there is a cycle in the WFG, then processes involved in the cycle will wait forever This is called a deadlock A simple approach to detecting deadlocks based on the idea of locally stable predicates is as follows We use a coordinator to collect information from processes in the system.

2 H2S + 2O2 SO4 + 2H+ G values ( 27.87) + (0) ( 744.6) + 2( 39.83) (assuming pH 7) f G = 796.39 kJ/reaction f

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Each process Pi maintains its local WFG, that is, all the edges in the WFG that, are outgoing from Pi It also maintains a bit charigedi, which records if its WFG has changed since its last report t o the coordinator The coordinator periodically sends a request message to all processes requesting their local WFGs On receiving this request,, a process sends its local WFG if the clrangedi bit is true and notmChariged message if changedi is false On receiving all local WFGs, the coordinator can combine them to form the global WFG If this graph has a cycle, the coordinator sends a message to all processes to send their reports again If chan,qedi is false for all processes involved in the cycle, then t,he coordinat,or reports deadlock.

Summary

In t>hisalgorit(hrr1,even though WFGs are constructed possibly on inconsistent global st,ates, we know, thanks to barrier synchronization, that there exists a consistent global state with the same WFG Therefore, any deadlock reported actually happened in a consistent, global state We leave the Java implementation of this algorithm as an exercise..

Because syndication feeds are XML formats, it s useful to consider XSL Transformations (XSLT) for use in normalization and conversion. It s likely you ve had some exposure to XSLT if you ve been keeping up with XML technologies though, so far, this book has managed to avoid it. This is because, for the most part, Python offers greater flexibility and conciseness as a general programming language. On the other hand, because the primary purpose of XSLT is to turn one XML document into another (the activity that makes up the core of feed normalization and conversion), its application would seem particularly apt here. And, if anything, it s a good medium within which to illustrate the nitty-gritty details involved in normalization and conversion.

Without spending too much time on the description of the concept, let s quickly define the constituents of the generic web presented in the figure The firm, of course, is the provider of products and services targeting at fulfilling the customer s requirement Competitors include those entities that provide a substitute offering, such as a product or service that pro vides the customer with the same or similar experience and utility as the firm s offering Suppliers are vendors that provide the inputs that in their aggregate make up the firm s products/services Service providers are those parties that fulfill critical activities that lie outside the firm s core competencies Retailers and resellers act as the distributors of the firm s products/services to the customer, whereas complementors provide a sep arate offer that can be used in combination with the firm s products.

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