Changes between Version 35 and Version 36 of ResourceManagement

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Timestamp:
07/02/10 00:37:16 (14 years ago)
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vuk (IP: 147.83.105.169)
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  • ResourceManagement

    v35 v36  
    11= FlexCRM Project = 
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    3 == Computing Resource Management: Motivation == 
     3SDR presents a hard real-time computing challenge with varying (computing) system conditions. The framework needs to track the states of the computing resources for being able to take advantage of the reconfiguration capabilities of mobile terminals and network elements. 
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    5 SDR presents a hard real-time computing challenge. Taking into account the evolution of wireless systems it is clearly stated that whereas spectrum efficiency increases lineally its requirements in computing resources increases exponentially. Therefore, the flexibility, based on the reconfiguration capacity of terminals and network equipment, is based on capability of their reconfiguration managers, which need to track the states of the computing resources. 
     5[[Image(CRM_org1.png, 400px, align=right)]] 
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    7 An SDR processing chain, SDR application or waveform, is the part of an SDR transceiver that is implemented in software. It can be understood as a set of concurrent processes that continuously process and propagate real-time data. Such a processing chain is not specifically tailored but rather executable on any general-purpose platform with sufficient computing capacity. Therefore, a mapping process, carrying out the task of assigning software modules to hardware resources, becomes the basis for the Computing Resource Management framework. Wireless and SDR systems, however, reveal specific aspects, essentially regarding flexibility and efficiency, that should be jointly considered: 
    8 [[Image(CRM_org1.png, 400px, align=right)]] 
    9   1. Time slot based division of the transmission medium (radio time slot); 
    10   2. Continuous data transmission and reception; 
    11   3. RAT-specific quality of service (QoS) targets; 
    12   4. Real-time computing requirements and limited computing resources; 
    13   5. Different constraints and computing loads for different RATs and radio conditions; 
    14   6. Dynamic reconfiguration of the protocol stack, either partial or total; 
    15   7. Heterogeneous multiprocessor execution platforms. 
     7Our computing resource management framework is modular. It features the computing system modeling on the one hand and management mechanisms on the other (Figure 3). The SDR computing system modeling monitors and models the SDR platforms' computing resources and the SDR applications' computing requirements. We, therefore, suggest equivalent metrics for modeling computing resources and requirements: million operations per second (MOPS) and mega-bits per second (Mbps) for modelling the processing and interprocessor data flow capacities and requirements. 
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    17 == Organization == 
     9The ALOE computing resource management is based on two simple time management principles: time slots and pipelining (Figure 4). This facilitates the synchronized execution of the waveform modules on distributed computing resources, while taking advantage of the continuous data flow that characterizes wireless communications. Based on these principles, ALOE applies general-purpose mapping algorithms and problem-specific cost functions. The cost function implements the computing resource management objective or policy while guiding the allocation of computing resources to computing requirements in a controlled manner. 
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    19 Our computing resource management proposal consists of several modules. The basis for the resource management is the [wiki:RealTimeManagement time management]. We divided it on a Computing System Modeling and a Management Mechanisms. 
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    21 [wiki:ResourceModels Computing Resource Modeling]. The SDR computing system modeling tracks the SDR platforms' available computing resource and the current SDR applications' computing requirements 
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    23 [wiki:BaseCRM_Algorithms Management Mechanisms]. The Management Mechanisms, based in the use of general-purpose mapping algorithms and specific cost functions, that reflects the applied management policies, assign (keeps track of and updates) the available computing resources as a function of the given computing requirements 
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