IOT

Edge Computing

The current activities in Internet of Things (IoT) are focused on architectures & protocols for efficient interconnection of things, infrastructure deployment and creation of value-added services. These activities are largely aided by cloud computing platforms which supports data analysis, management, repository, middleware, APIs etc. But cloud based IoT deployments faces challenges for supporting real time IoT services and providing better consumer experience. Responding to these consumer needs, we have started witnessing a paradigm shift. The capabilities of cloud computing platforms are being pushed to the edge of the networks paving way for Edge Computing (EC). Due to dense geographical distribution, proximity to end-users, support for high mobility and open platform, EC can support applications and services with ultra-low latency and improved QoS. Thus EC is becoming an important enabler of consumer centric IoT applications and services that demand real-time operations. Standard development organizations like ETSI have also recognized the benefits IoT & Mobile EC can bring to the consumers. Potential applications for EC enabled IoT include smart mobility, emergency response, smart cities, video and location based analytics, edge caching and environmental monitoring.

EC presents unique set of research and engineering challenges as mentioned below.

  1. Programmabiliity - In EC scenarios, computation is offloaded from the cloud, and the edge nodes are most likely heterogeneous platforms. In this case, the runtime of these nodes differ from each other, and the programmer faces huge difficulties to write an application that may be deployed in the heterogeneous Edge computing platforms.
  2. Naming - In Edge computing, one important assumption is that the number of things is tremendously large. Atop the edge nodes, there are a lot of applications running, and each application has its own structure about how the service is provided. Similar to all computer systems, the naming scheme in Edge computing is very important for programing, addressing, things identification, and data communication. However, an efficient naming mechanism for the Edge computing paradigm has not been built and standardized yet. Edge practitioners usually needs to learn various communication and network protocols in order to communicate with the heterogeneous things in their system. The naming scheme for Edge computing needs to handle the mobility of things, highly dynamic network topology, privacy and security protection, as well as the scalability targeting the tremendously large number of unreliable things. Traditional naming mechanisms such as DNS and URI (Uniform Resource Identifier) satisfy most of the current networks very well. However, they are not flexible enough to serve the dynamic Edge network since sometimes most of the things at Edge could be highly mobile and resource constrained. Moreover, for some resource constrained things at the Edge of the network, IP based naming scheme could be too heavy to support considering its complexity and overhead. New naming mechanisms such as Named Data Networking (NDN) could be applied in such case.
  3. Data abstraction
  4. Service management
  5. Security, privacy and trust
  6. Performance evaluation
  7. Strategies for data caching at edge nodes

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