| 1. |
- Hansen, Jeffery, et al.
(författare)
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Adaptive Flow Control for Enabling Quality of Service in Tactical Ad Hoc Wireless Networks : TECHNICAL REPORT, CMU/SEI-2010-TR-030, ESC-TR-2010-030
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Wireless networks for emergency responders and military personnel operating in tactical situations are often assembled without any preexisting infrastructure (i.e., ad hoc) and are subject to changing topology as nodes enter or leave service or move (i.e., are mobile) in the environment. These networks often have lower-than-optimal bandwidth and can see further bandwidth reductions due to disadvantageous topologies and other factors. In addition, needed applications must compete for possibly diminishing bandwidth. As a result, such networks are frequently oversubscribed: they cannot fully meet the quality of service (QoS) expectations of all applications. This report provides an overview of approaches for satisfying QoS expectations in ad hoc wireless networks assembled to support high-criticality crisis and tactical scenarios. It illustrates that these approaches are adaptations of approaches used in wired (often fixed) infrastructures where bandwidth is known and interference is not the norm. It documents and provides experimental evidence for the Adaptive QoS (AQoS) approach that allows applications to adapt bandwidth demand to conditions without the need to know, estimate, or predict available bandwidth. AQoS informs applications that oversubscription is occurring, thereby allowing them to continue to operate, albeit at diminished rate or capacity, and meet mission needs.
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| 2. |
- Hansen, Jeffery, et al.
(författare)
-
Adaptive Quality of Service in Ad Hoc Wireless Networks
- 2012
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Ingår i: IEEE Wireless Communications and Networking Conference (WCNC). - 9781467304368 ; , s. 1749-1754
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Konferensbidrag (refereegranskat)abstract
- In high criticality crisis scenarios, such as disaster management, ad hoc wireless networks are quickly assembled in the field to support decision makers through situational awareness using messaging-, voice-, and video-based applications. These applications cannot afford the luxury of stalling or failing due to overwhelming bandwidth demand on these networks as this could contribute to overall mission failure. This paper describes an approach for satisfying application-specific Quality of Service (QoS) expectations operating on ad hoc wireless networks where available bandwidth fluctuates. The proposed algorithm, D-Q-RAM (Distributed QoS Resource Allocation Model) incorporates a distributed optimization heuristic that results in near optimal adaptation without the need to know, estimate, or predict available bandwidth at any moment in time.
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| 3. |
- Hansen, Jeffery, et al.
(författare)
-
Resource Allocation in Dynamic Environments : TECHNICAL REPORT, CMU/SEI-2012-TR-011, ESC-TR-2012-011
- 2012
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This technical report examines two challenges related to resource allocation that can negatively affect system operation in a dynamic environment, where warfighter needs for resources, resource availability, environmental effects, and mission conditions can change from moment to moment. The first challenge occurs when warfighters overstate their individual needs of a shared resource, leading to inefficient allocation. Overstatement may bring local optimization; however, it can cause global inefficiencies that result in a detriment to overall mission success. This challenge is addressed by using computational mechanism design, more specifically, the dynamic VickreyClark-Groves allocation mechanism. The second challenge involves resource availability that may change frequently. Such is the case in a wireless mesh network where routes and bandwidth may vary over even small intervals of time. In such a case, an adaptive quality of service (AQoS) approach is used, and the available resource is allocated using the Dynamic QoS-based Resource Allocation Model (DQ-RAM). Computational mechanism design is used to allocate sensors, and the AQoS approach allocates the available network bandwidth in a way consistent with the sensor allocation, providing an approach for dealing with resource allocation and adaptation in a dynamic environment. Initial experimental results of applying the approach are reported.
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