Software limitations in .NET framework

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18.2.1.5 Software limitations
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The most obvious limitation on real-time software under Symbian OS is that, with the exception of the bounded kernel services, most Symbian APIs do not have bounded execution times. Non-kernel APIs such as le system access and other system servers generally do not provide any real-time guarantees. One (but not the only) reason for this is that most of them rely on unbounded kernel services, most notably memory allocation and freeing. When you are writing real-time software to run under EKA2, the rst thing to bear in mind is that the standard dynamic memory allocation primitives do not provide any real-time guarantees. There are two main reasons for this: Firstly, the default algorithm used to manage an application s heap memory (the RHeap class) is address-ordered rst t, using a simple linked list of free cells. It may need to search many free cells to nd one that is capable of satisfying an allocation request, or to nd the correct place in which to insert a cell that is being freed. Secondly, if there is no free cell large enough to satisfy a request, the algorithm requests more memory from the global free page pool. Even though a request for a single page can be completed in a known time, the pool is protected by a mutex which could be held for a long period if another thread is also performing memory allocation or freeing. This means that accesses to the global pool cannot be performed in a known time. There are two main techniques for avoiding this problem. The rst is to avoid dynamic memory management altogether in time-critical sections of code. Instead you should allocate all memory blocks at initialization time and free them when the application or operation terminates.
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The second technique is to replace the standard RHeap allocator with a custom allocator designed to offer predictable execution times for example an allocator based on a small number of xed block sizes. The allocator will need to be seeded with a xed amount of memory from the global pool when the real-time application initializes. Why didn t Symbian provide such an allocator The address-ordered rst- t algorithm used by the standard Symbian OS RHeap class is a good generalpurpose algorithm that provides low memory overhead and acceptable performance for most applications without making any assumptions about the size and pattern of allocations made by the application. Custom allocators can take advantage of their knowledge of the particular application involved, especially of the sizes of allocations made, and can give real-time guarantees without compromising on space ef ciency. Alternatively, they may trade space ef ciency for bounded execution time. The custom allocator approach has the advantage that any standard library functions used in the same thread or process also use the predictable algorithms. Of course this doesn t help with allocations occurring in the kernel or in server processes; these must simply be avoided in time critical code. Another fundamental limitation of Symbian OS for real-time software is that it is an open OS. Subject to the restrictions of platform security, any code, even that which is written long after the mobile phone was designed and built, may be loaded onto the phone and executed. There is no way for programs to declare real-time deadlines to the OS, and no way for the OS to make use of such information. The user could run many applications, all requiring real-time guarantees, and there is no way for the OS to indicate that it cannot provide the required guarantees to all the applications. In the strictest sense, real-time guarantees can only be given to code supplied with the mobile phone by the manufacturer, and even then only if aftermarket applications are restricted to the lower levels of the thread priority spectrum. As well as ensuring that your code runs quickly enough to deliver acceptable results without consuming too much power, it s also essential to ensure that it doesn t damage system response times. There are several places where latency can be measured, and at all of these it can prove a problem. These locations are in interrupt service routines (ISRs), delayed function calls (DFCs and IDFCs) and user threads, in order of increasing response time (illustrated in Figure 18.1). The vast bulk of code in the system runs in one of these three environments, so it s very important not to slow down any of them unduly. The basic problem is how to enforce and maintain scheduling priority over short timescales This is the priority inversion problem and hinges on one question: how long can an urgent process, triggered by some event that is not directly associated with program execution, be delayed because the system is busy with a less urgent task
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