Memory management strategies

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  • (BQ) Part 1 book "Operating system concept" has contents: Introduction, system structures, process concepts, multithreaded programming, process scheduling, synchrozination, deadlocks, memory management strategies, virtual memory management.

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  • In this chapter, we discuss various ways to manage memory. The memory- management algorithms vary from a primitive bare-machine approach to paging and segmentation strategies. Each approach has its own advantages and disadvantages. Selection of a memory-management method for a specific system depends on many factors, especially on the hardware design of the system. As we shall see, many algorithms require hardware support, leading many systems to have closely integrated hardware and operating-system memory management.

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  • In chapter 7, we discussed various memory-management strategies used in computer systems. All these strategies have the same goal: to keep many processes in memory simultaneously to allow multiprogramming. However, they tend to require that an entire process be in memory before it can execute. Virtual memory is a technique that allows the execution of processes that are not completely in memory. In this chapter, we discuss virtual memory in the form of demand paging and examine its complexity and cost.

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  • Chapter 11 - Memory management. This chapter discusses the implementation of dynamic arrays and other objects using conventional techniques for managing heap memory. Especially important in this context is the notion of heap overflow, along with strategies for dealing with heap overflow when it occurs at run time. We discuss three key algorithms for heap memory management, which are affectionately known as garbage collection algorithms.

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  • This chapter discusses the implementation of dynamic arrays and other objects using conventional techniques for managing heap memory. Especially important in this context is the notion of heap overflow, along with strategies for dealing with heap overflow when it occurs at run time. We discuss three key algorithms for heap memory management, which are affectionately known as garbage collection algorithms.

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  • The goal of autonomic computing is the reduction of complexity in the management of large computing systems. The evolution of computing systems faces a continuous growth in the number of degrees of freedom the system must manage in order to be efficient. Two major factors contribute to the increase in the number of degrees of freedom: Historically, computing elements, such as CPU, memory, disks, network and so on, have nonuniform advancement.

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  • Chapter 10 - Function implementation. The stack implementation of function call and return is a central topic deserving deeper study. Moreover, strategies for the management of another memory area called the heap, are important to the understanding of dynamic objects like arrays. Chapter 10a presents the following content: Function declaration and call in clite, completing the clite type system, semantics of call and return.

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