Binary Exponential Backoff Algorithm was chosen to dynamically adapt to the number of stations trying to send. If the randomization interval for all collision was 1023 slots, the chance of two stations colliding for a second time  would be negligible, but the average wait after a collision would be hundreds of slot times, introducing significant delay. On the other hand, if each station always delayed for either 0 or 1 slot, then if 100 stations ever tried to send at once, they would collide over and over until 99 of them picked 1 and the remaining station picked 0. This may take years. But having the randomization interval grow exponentially as more and more consecutive collisions occur, the algorithm ensures a low delay when only a few stations collide but also ensures that the collision is resolved in a reasonable interval when many stations collide. Truncating the backoff at 1023 keeps the bound from growing too large.

An application that exists in a distributed environment, such as the Internet. A Web service accepts a request, performs its function based on the request, and returns a response. The request and the response can be part of the same operation, or they can occur separately, in which case the consumer does not need to wait for a response. Both the request and the response usually take the form of XML, a portable data-interchange format, and are delivered over a wire protocol, such as HTTP.

An object used by a servlet to track a user's interaction with a Web application across multiple HTTP requests. What is session bean

An enterprise bean that is created by a client and that usually exists only for the duration of a single client-server session. A session bean performs operations, such as calculations or database access, for the client. Although a session bean can be transactional, it is not recoverable should a system crash occur. Session bean objects either can be stateless or can maintain conversational state across methods and transactions. If a session bean maintains state, then the EJB container manages this state if the object must be removed from memory. However, the session bean object itself must manage its own persistent data.

It guarantees that the spurious tuple generation does not occur with respect to relation schemas after decomposition.

A Checkpoint is like a snapshot of the DBMS state. By taking checkpoints, the DBMS can reduce the amount of work to be done during restart in the event of subsequent crashes.

i. Bad normalization

ii. Theta joins

iii. Updating tables from join

a) i & ii b) ii & iii

c) i & iii d) ii & iii

(a) i & ii because theta joins are joins made on keys that are not primary keys.