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Computer System Software
Published in Brian Roffel, Patrick Chin, Computer Control in the Process Industries, 2017
Memory partitions are fixed in size, but can be different in size. As an example, partition 1 could be 4k, partition 2 could be 8k, and so forth. Programs with priority 1 can run in all partitions; programs with priority 2 can run in partition 2 and higher. Hence, the partition structure is determined by the total available memory and by the size of the programs. If we have a 14k program and want it to be able to run in at least two partitions, these two partitions need to be 14k or more. Background programs can run in the highest area in memory. The size of the background partition is usually fairly large. If all partitions in memory were in use and partition 2 and 5 were to be freed due to completion of the task, a new task could only be started if it fits into partition 2 or 5. However, if partition 2 and 5 were joined together, a much bigger task could be processed. To make this possible, tasks are shifted in memory after previous tasks are finished or suspended. This shifting or relocation can be done in two different ways: hardware relocation, in which each task is started at location zero and where a computer hardware register keeps track of the real location. Upon a relocation the register is used to update the new address at which a task is running. In other systems the relocation problem is solved via software. Since each reference toward a memory location is relative to the start of a program, the program can run at any location without a problem. There are a number of other techniques available for optimal use of computer memory, e.g., segmentation and virtual memory techniques.9,10
Building Reconfigurable Systems Using Commercial FPGAs
Published in Juan José Rodríguez Andina, Eduardo de la Torre Arnanz, María Dolores Valdés Peña, FPGAs, 2017
Juan José Rodríguez Andina, Eduardo de la Torre Arnanz, María Dolores Valdés Peña
Module relocation is a clear advantage in systems based on regular slots since the same function may be allocated into different regions, providing additional flexibility, a certain degree of fault tolerance (a function may be moved from a faulty to a fault-free region), and memory footprint savings, since just one bitstream is required to support all destinations, instead of one for each possible destination.
R
Published in Phillip A. Laplante, Dictionary of Computer Science, Engineering, and Technology, 2017
relocation the operation performed by a linker or loader which modifies relocatable values to bind them to actual memory addresses. Note that a linker may compute relative relocations which are not bound until the loader loads the program.
A static relocation strategy for electric car-sharing systems in a vehicle-to-grid framework
Published in Transportation Letters, 2021
Leonardo Caggiani, Luigi Pio Prencipe, Michele Ottomanelli
One of the major current transport challenges is trying to reduce traffic congestion and emission of pollutants, as it was treated in the 2015 United Nations Climate Change Conference in Paris. A possible solution could be improving the practice of vehicles sharing, implementing the ‘Mobility as a Service’ (MaaS) concept, which offers convenient door-to-door transport without the need to own a private vehicle (Kamargianni et al. 2016). Car-Sharing Systems (CSSs) can play an essential role in the MaaS if they are integrated with other sustainable systems (e.g. public transport, bike-sharing, car-pooling, etc.). A CSS is generally based on a car fleet and on a restricted number of users having access to cars for short-term periods by paying per use (Bardhi and Eckhardt 2012). There are two types of CSSs: station-based systems and free-floating systems. The reference model is station-based. In this case, a user can pick-up and drop-off a car only within stations. On the other hand, in the free-floating case, more flexibility is allowed. This happens because free-floating systems define a geo-fence through which the rent and the return of vehicles very close to the demand point is possible, without the necessity to pass by a station before or after the trip (Herrmann, Schulte, and Voß 2014). The most attractive CSSs give users the opportunity to make one-way trips. One-way operations, as well as the imbalance of vehicles demand, could generate some problems both at trip origin (pick-up station) and at trip destination (drop-off station). Among the possible issues, a situation in which vehicles are accumulated to stations where they are not needed may occur, while at the same time there could be vehicle shortage at stations where more vehicles are required (Barth, Todd, and Xue 2004; Kek et al. 2009; Nair and Miller-Hooks 2011; Di Febbraro, Sacco, and Saeednia 2012; Boyacı, Zografos, and Geroliminis 2015; Schmöller et al. 2015; Huang, Correia, and An 2018). Due to this unbalanced status between stations, some users could leave the system (lost users) because they may not find a car/parking place available near their origin/destination. Vehicle relocation, i.e. transfer of vehicles from stations with high vehicle accumulation to stations with low vehicle accumulation, is a technique that has been proposed to reduce the imbalance of one-way CSSs (Jorge, Correia, and Barnhart 2014). Two different relocation approaches were proposed: user-based and operator-based relocation. User-based strategies offer incentives to customers for changing their travel behavior. In contrast, operator-based strategies provide vehicle redistributions performed by operators: during the night, when the demand is negligible (static relocation) or during the whole day, when the demand changes depending on time (dynamic relocation). For a detailed overview of the different one-way CSSs vehicle relocation problem approaches, see Weikl and Bogenberger (2013) and Illgen and Höck (2019).