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Networks consist of connections between computers and devices These connections are most commonly physical connections, such as wires and cables, through which electricity is sent However, many other media exist For example, it is possible to use infrared and radio as a communication medium for transmitting data wirelessly, or fiber-optic cables that use light rather than electricity Such connections carry data between one point in the network and another This data is represented as bits of information (either "on" or "off," a "zero" or a "one") Whether through a physical medium such as a cable, through the air, or using light, this raw data is passed across various points in the network called nodes; a node could represent a computer, another type of hardware device such as a printer, or a piece of networking equipment that relays this information onward to other nodes in the network or to an entirely different network Of course, for data to be successfully delivered to individual nodes, these nodes must be clearly identifiable

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A collection of tasks that can execute concurrently (see the Task Decomposition pattern) A data decomposition corresponding to the collection of concurrent tasks (see the Data Decomposition pattern) Dependencies among the tasks that must be managed to permit safe concurrent execution

SelectExpression is the text of your query and is the only required parameterThere is no DomainName parameter; however, the query must apply to a single domainThe domain is passed within SelectExpression in the FROM clause If you need to query multiple domains, you must submit a separate query for each domainThere is no way to search multiple domains with one Select operationThe details of SelectExpression are covered in 4, A Closer Look at Select

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Each node in a network is typically represented by an address, just as a street name and number, town or city, and zip code identifies individual homes and offices The manufacturer of the network interface card (NIC) installed in such devices is responsible for ensuring that no two card addresses are alike, and chooses a suitable addressing scheme Each card will have this address stored permanently, so that it remains fixed it cannot be manually assigned or modified, although some operating systems will allow these addresses to be faked in the event of an accidental conflict with another card's address Because of the wide variety of NICs, many addressing schemes are used For example, Ethernet network cards are assigned a unique 48-bit number to distinguish one card from another Usually, a numerical number is assigned to each card, and manufacturers are allocated batches of numbers This system must be strictly regulated by industry, of course two cards with the same address would cause headaches for network administrators The physical address is referred to by many names (some of which are specific to a certain type of card, while others are general terms), including:

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As addressed in the Group Tasks and Order Tasks patterns, the starting point in a dependency analysis is to group tasks based on constraints among them and then determine what ordering constraints apply to groups of tasks The next step, discussed here, is to analyze how data is shared among groups of tasks, so that access to shared data can be managed correctly Although the analysis that led to the grouping of tasks and the ordering constraints among them focuses primarily on the task decomposition, at this stage of the dependency analysis, the focus shifts to the data decomposition, that is, the division of the problem's data into chunks that can be updated independently, each associated with one or more tasks that handle the update of that chunk This chunk of data is sometimes called task local data (or just local data), because it is tightly coupled to the task(s) responsible for its update It is rare, however, that each task can operate using only its own local data; data may need to be shared among tasks in many ways Two of the most common situations

These addresses are used to send information to the appropriate node If two nodes shared the same address, they would be competing for the same information and one would inevitably lose out, or both would receive the same data Often, machines are known by more than one type of

The response data for the Select operation is as follows:

In addition to task local data, the problem's data decomposition might define some data that must be shared among tasks; for example, the tasks might need to cooperatively update a large shared data structure Such data cannot be identified with any given task; it is inherently global to the problem This shared data is modified by multiple tasks and therefore serves as a source of dependencies among the tasks Data dependencies can also occur when one task needs access to some portion of another task's local data The classic example of this type of data dependency occurs in finite difference methods parallelized using a data decomposition, where each point in the problem space is updated using values from nearby points and therefore updates for one chunk of the decomposition require values from the boundaries of neighboring chunks

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