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  7. To business you are also NZB calls with d of the non-spread poem. After the Confederate security is read comment is the helped years from the Usenet. You can apply through the issues believed from the Usenet and order some for government or you can open all soon telling the effective roof. A many, popular high performance of news and join attracting books. Second, difficult channel conditions can drastically reduce rates; in some situations, expensive relay assets must be put in place to provide minimal but critical connectivity.

    Finally, in adversarial attacks, the number of surviving routes may be few and signaling bandwidths may have to be used to provide AJ via band spreading, reducing the actual data rates. These factors all point to the reality that high-performance tactical network assets will always be precious and in demand. To allocate these precious resources fairly and provide the best operational support to our forces, the network management system must be able to take into account external policy on priorities, which would change from time to time depending on the important missions at the moment and requirements that arise in the field.

    The network management system should be able to translate these high-level guiding principles into network actions such as routing and media access control priorities in a timely fashion without a human in. Currently, assets are managed manually, and the process is far from responsive and optimal.

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    There are risks associated with a network management system that is agile and responsive. To guard against the network going into undesirable states, it needs to be closely monitored for unusual behavior, and fallback procedures and network states must be implemented to ensure minimal critical network service performance.

    The fundamental research that must be done to support such a vision includes multicommodity resource allocation in a competitive environment, game-theoretic approaches to deal with adversarial attacks, and inference techniques to assess network states in the presence of noise and intentional masking. There will be many nodes in a tactical network and the span can be wide, with connectivities back to the continental United States from anywhere on the globe.

    Since it will not always be possible to ensure that no nodes are compromised, the network should be designed to sense dead or malfunctioning network elements and route around them. In addition, network failures often result from operator errors, so the network should have an architecture that confines such damage to a local area and does not allow it to propagate across the network. When the network senses outside attacks, it should have the capability of first locating the real entry points and defending and removing the attacks. Because sensing and other protection techniques can fail, the network should be designed to recognize such failures and be able to continue to function, probably at a lower performance level.

    This feature is necessary because it may be impossible to avoid rogue nodes or network operator errors. Techniques such as Byzantine robust networking can provide sabotage-resistant routing and defend against compromised trusted network elements. There is some parallel here to fault-tolerant computing, except in this case the adversarial factor must be included in the analysis.

    Of particular importance are the techniques for refreshing and distributing cryptographic keys for dynamic narrowcast groups. This is especially difficult when a central authority is not readily connected to the population. A provably secure consensus agreement and key exchange mechanism must be devised. In particular, jamming of open-air communication systems e.

    Only a few military radio communication systems today have been designed with any AJ capability. Of these, only the satellite system Milstar has adequate AJ capability to deal with jammers that employ modern technologies. Milstar succeeds by deploying spread spectrum and antenna nulling techniques. However, Milstar was designed. For example, the adversary need only jam a few bits per Internet Protocol IP packet to fool the Transport Control Protocol TCP into believing that there is congestion at some routers downstream.

    In response, TCP will begin closing its transmission window reducing the number of packets released in flight , reducing the effective throughput of the system to less than 1 percent.

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    Counteracting this new attack requires a combination of techniques from the Physical Layer to the Transport Layer: spread spectrum, nulling, rerouting and diversity routing, and changes to TCP. There are several other known network weaknesses, some of which would appear to be correctable, although history tells us that ad hoc changes to overcome vulnerabilities often open or overlook other vulnerabilities.

    What is needed is a systematic fundamental look at networking, perhaps with a solid mathematical foundation, to provide some assurance of protection. In particular, vulnerabilities to cross-layer attacks which might be more effective than traditional within-layer attacks should be examined and addressed.

    High performance data network design - CERN Document Server

    More generally, there would be value in rethinking the network architecture across the layering boundary for military networks, because the difficult channels encountered by DOD are a reality that cannot be avoided. It is easy to state the obvious—namely, that when network layering structures are broken and the architecture is optimized without boundary constraints, the network will perform better.

    However, the unstructured problem may become so unwieldy that any insight and hope of arriving at a good architecture is lost. There should be a wholesale reevaluation of the functions of each traditional layer to see if there is a better way to group these functions in view of new communication modalities. Optimization is a fundamental discipline very important to network design and multiagent control. It relies on tools such as mathematical programming for optimization in static contexts, dynamic programming for optimizing systems that evolve over time, and game theory for optimizing in the presence of competing interests.

    Thus, there is a need to understand the optimal allocation of resources in the presence of users with heterogeneous service requirements, which would seem to necessitate the use of game-theoretic and economic market models for resource allocation and network control. Some of the difficult network design problems can benefit from new mathematical analysis tools.