Distributed Computing
Distributed computing studies the theory and methods to solve computational problems in distributed systems. There are many interesting and important problems that can be solved efficiently in distributed systems, such as data gathering in wireless sensor
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Distributed Computing
Abstract Distributed computing studies the theory and methods to solve computational problems in distributed systems. There are many interesting and important problems that can be solved efficiently in distributed systems, such as data gathering in wireless sensor networks, computing graph properties, and leader election in a distributed system. In this chapter, we introduce the elementary concepts about distributed computing and some of the important components of distributed computing. In Sect. 2.1, we introduce the concept of distributed computing and present an example to illustrate it. Then, we present the communication models that are commonly utilized in Sect. 2.2, show the incompleteness of information in Sect. 2.3, and discuss the aspect of timing which plays an important role in distributed computing in Sect. 2.4.
2.1 What is Distributed Computing? Distributed computing studies how to solve computational problems in distributed systems or environments. Generally speaking, an entity in a distributed system can compute its tasks completely locally against its “individual” goals. An analogy would be that each individual has his own will and sentiments about certain public events. However, these entities can also cooperate to solve global computational problems which are tough or impossible for a single entity to handle, even though they may not know the others’ information. For example, all individuals can contribute their strength in crowdsourcing to provide some common needed services or to achieve some common goal [1, 2, 6]. We use a simple example of wireless sensor networks to explain distributed computing. As illustrated in Fig. 2.1, 9 sensors are deployed in the environment to detect the temperature. The goal is to find out the highest temperature in the area at the base station through the sensors. As shown in the figure, the sensors form a wireless network where any two sensors are supposed to be connected if they are within each other’s range of communication. Each sensor node can detect the temperature locally and then share this local data by communicating with nearby neighboring sensors. The 9 sensors can sense different temperature data and after receiving the others’ data © Springer Nature Singapore Pte Ltd. 2017 Z. Gu et al., Rendezvous in Distributed Systems, DOI 10.1007/978-981-10-3680-4_2
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2 Distributed Computing
Fig. 2.1 An example of computing the maximum temperature in a wireless sensor network
Fig. 2.2 An example of update dating when we are to compute the maximum temperature through the wireless sensor network
(the temperature data), each sensor can compute which temperature is the highest among all neighbors and then update the data. In Fig. 2.2, sensor 4 will update the local highest temperature data to 42 since it can collect four values {19, 31, 38, 42}. Similarly, sensor 5 will update the local temperature to 39 and sensor 9 to 41. However, having updated its data, a sensor would communicate its updated data with the neighbors again. For exampl
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