In computer networking, resilience is the ability to "provide and maintain an acceptable level of service in the face of faults and challenges to normal operation." Threats and challenges for services can range from simple misconfiguration over large scale natural disasters to targeted attacks. As such, network resilience touches a very wide range of topics. In order to increase the resilience of a given communication network, the probable challenges and risks have to be identified and appropriate resilience metrics have to be defined for the service to be protected.
The importance of network resilience is continuously increasing, as communication networks are becoming a fundamental component in the operation of critical infrastructures. Consequently, recent efforts focus on interpreting and improving network and computing resilience with applications to critical infrastructures. As an example, one can consider as a resilience objective the provisioning of services over the network, instead of the services of the network itself. This may require coordinated response from both the network and from the services running on top of the network.
These services include:
supporting distributed processing
supporting network storage
maintaining service of communication services such as
video conferencing
instant messaging
online collaboration
access to applications and data as needed
Note that resilience and survivability are interchangeably used according to the specific context of a given study.
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A computer network is a set of computers sharing resources located on or provided by network nodes. Computers use common communication protocols over digital interconnections to communicate with each other. These interconnections are made up of telecommunication network technologies based on physically wired, optical, and wireless radio-frequency methods that may be arranged in a variety of network topologies. The nodes of a computer network can include personal computers, servers, networking hardware, or other specialized or general-purpose hosts.
Students will learn the core concepts and techniques of network analysis with emphasis on causal inference. Theory and application will be balanced, with students working directly with network data th