Essentially a type of data network, cognitive networks have grown to prominence in recent years for its extensive use in communication networks. This networking technique combines cutting-edge technologies from different research areas, viz., computer network, network management, machine learning, and knowledge representation, to address issues current networks are facing.
Cognitive networks employ a cognitive process that can not only perceive current network conditions, but also plan, decide, and act on those conditions. Besides, this kind of networks learn from the consequences of its actions, while following the end-to-end goals. The loop, also known as the cognition loop can sense the environment and plan actions, based on the inputs obtained from sensors and network policies.
There are limitations to the present technology used for data networking. Limitations surrounding response, state, and scope mechanism are the chief networking concerns which bother users. These limitations may lead to incapability of network elements such as nodes, protocol layers, and policies. Cognitive Networking plays a crucial role here by replacing conventional networks with modern and intelligent ways of communication, information, and learning.
The concept of cognitive networking grew out of research conducted in cognitive radios, which combines intelligent, or cognitive processing with a platform. Besides, sensing the radio environment, the platform reflects ability to react and change its configuration.
Advantages of Cognitive Networking
Cognitive networking technique can be applied across any type of network– fixed or wireless, thus offering better protection against security attacks and network intruders. Essentially, this technique proves useful for both service operators and customers.
Such networks can adapt their operational parameters to respond to user’s needs, or to address changing environmental conditions. Moreover, they can learn from these adaptations, and exploit the knowledge obtained to execute decisions in future. Cognitive networking gives devices the ability to transmit more data, while reducing energy consumption, and efficiently using available bandwidth.
With the passage of time, researchers are stumbling upon many possible civilian and commercial applications of flexible and adaptable networks. Cognitive Networking is the future, allowing users to focus on core activities, while all the network configuration and management is automated. The space will witness huge competition in the years to come, as companies like Google among others are exploring the ideas of integrating an intelligence or learning system in networks.
Is Infinera’s Instant Network billing solution based on Cognitive Networking?
The industry has made significant strides in the field of SDN, reflecting progress around virtualizing and controlling Layer 1/2/3 services over a fixed amount of optical capacity. Only by installing additional network hardware, the capacity can be increased. Infinera, a provider for intelligent transport networks, recently announced the launch of its Instant Network billing solution. The offering was touted as the “the next generation of software defined capacity (SDC) for cloud scale networks and a necessary foundation for cognitive networking.”
The Instant Network offering would enable service providers to activate capacity when revenue-generating services demand it, reduce capital expenditures by diminishing idle optical network capacity, or even lower business risk by shrinking the time between paying for capacity and activating revenue-generating services.
This move towards unifying cognitive networking will allow service providers to equip their optic fiber network with Infinera photonics to a level of capacity greater than what they use, or pay for. “Since 2012, Infinera has been offering Instant Bandwidth since, when it introduced a single optical line card supporting five 100Gbps channels,” comments Pravin Mahajan, Director of Product and Corporate Marketing, Infinera.
Challenges of implementing Cognitive Networks
Undoubtedly, cognitive networking proposes numerous advantages over conventional networks. However, there are few challenges which must be addressed before we realize comprehensive benefits of implementing the technology. System stability, resilience, correctness, and robustness are some of the existing challenges enterprises are striving to address. The characteristic ability of cognitive networks to adapt easily to environmental changes will not only provide consistency, but also help in maintaining optimality of the system.
Additionally, enterprises find it a challenging job to combine cognitive networking with “Internet of Things.” Connecting networks wirelessly to electronics and software, without using human interaction can be utilized to power several smart applications, such as networking air and water quality monitors, tracking devices’ energy consumption, and optimizing the operation of next-generation “smart grid” electricity systems.
Another primary concern perturbing researchers is the need to address security and privacy. These intelligent networks will be able to make decisions on their own, and connect to whatever network they see fit. This could result in compromise of personal or sensitive information. Thus, security surfaces as a chief concern that needs to be addressed before we implement such networks comprehensively.
Most importantly, cognitive networks must undergo laborious and careful engineering to assure the system’s validity, consistency, and correctness from the time of its development, until operation and removal. Monitoring is also a chief aspect about cognitive networking, and is performed to ensure that the system functions properly.
Enabling the vision for a Cognitive Network
The software defined networks existing today allow network links at layer 2 or layer 3 to be configured on the fly through human intervention, or by using a software through an API. Through cognitive networking, AI will be easily able to recognize the network state and usage patterns. This will enable easy reconfiguration of such networks.
The intelligence associated with Cognitive Networking will assist towards predicting and optimizing data transfer. This transfer will consider aspects such as historical information, quality of service, needs of users, and the current state of the network. Furthermore, recommendations about optical network configurations can also be furnished to the user.
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