Internet Of Things: New Architecture Needed

Today's Internet architecture isn't ready for the scale of what the IoT should become. Here's a proposal for something better.

Cristian Borcea, Associate Chair, Department of Computer Science, New Jersey Institute of Technology

June 26, 2014

6 Min Read

The vision everyone keeps touting for the Internet of Things, where billions of devices are sharing information and completing tasks to improve the efficiency of daily life, relies on access to a planetary-scale Internet. Unfortunately, today's architectures can't handle the needs that the Internet of Things will demand.

In the near future, the number of devices connected to the Internet of Things (IoT) will reach 26 billion devices, according to Gartner, and produce $300 billion in revenue. Some of the devices that will participate in the IoT are sensors and actuators in smart cities, smart tags on many familiar objects, wearable health monitoring sensors, smartphones, intelligent cars, and smart home appliances. In the not so distant future, IoT will incorporate many types of robots -- domestic, flying drones, and even bee-size flying robots. The changes to our daily life will be immense. For example, IoT will lead to a more precise and greener management of power and water distributions in smart cities and improvements in healthcare such as stopping the spread of epidemic diseases.

However, today's technology isn't ready for the massive scale and highly dynamic nature of the future IoT, the huge amounts of data streamed from the physical world, and the new communication patterns it creates. We need novel programming, content delivery, and network management approaches. What follows is a proposed, still-developing framework for such a global, Internet of Things architecture.

One major problem with the current IoT architectures is they're designed for relatively small scale IoT islands -- closed-looped networks, such as a power plant operator pulling data from a turbine -- under proprietary protocols. Densely deployed "things" can't collaborate dynamically across these "islands" to execute distributed tasks that involve sensing, actuating, and computing.

So, how can we better facilitate the current state of IoT to reach its full potential? We must rethink the intelligence embedded in the IoT architecture.

[What about security? Read IoT: Get Security Right The First Time.]

In collaboration with the National Institute of Informatics (NII) in Japan, I've been researching how to leverage cloud computing technologies and software defined networks (SDN) to promote effective and efficiently distributed IoT services. This investigation has led me to believe that the future of IoT should evolve organically on top of the existing Internet and implement a novel distributed intelligence architecture called 3DIA -- a three tiered "distributed intelligence architecture."

3DIA is based on three design principles:

  1. Distributed execution of IoT services

  2. IoT networking inspired by SDN principles

  3. Pervasive cloud-based support for IoT

By implementing 3DIA, Internet of Things devices will be able to execute distributed sensing and computing services with help from the cloud, which can address the problems related to availability, resource limitation, bandwidth, latency, and management.

3 tiers of a gloabl network
3DIA is broken down into three tiers: global intelligence, regional intelligence, and local intelligence. Existing efforts have tackled Internet of Things issues at the regional and local tiers.

Global: The top tier provides global intelligence in the cloud for scalable services, network management, service programming, and device interaction. For example, this tier would allow for global coordination among IoT devices in a large city (e.g., assets belonging to public utilities, various city agencies, and individual users) and for efficient distributed service execution. Currently, this is not possible because different IoT networks don't interact with each other. Furthermore, the global tier would simplify the interactions between users and services by providing a highly available service end point in the cloud. The problems inherent to the distributed nature of services, such as device failures or disconnections due to mobility, would be transparent to users who interact with this service end point.

Regional: The middle tier provides regional intelligence to effectively handle the IoT dynamics, network traffic engineering, and wireless resource allocation, which is implemented at wireless access networks that are enhanced with computing and storage resources to form a new type of pervasive cloud infrastructure We call these "stratus clouds." This tier would, for instance, provide effective management of location dependent resources. One typical example of such resources is scarce radio resources, which have a strong dependence on location. In this case, the stratus clouds will run software defined radio (SDR) protocols that help with radio spectrum allocation. For example, this could be useful in a disaster scenario where many users will crowd certain regions trying to evacuate and efficient spectrum allocation is necessary to avoid interference. The stratus cloud would enable the deployment of this type of regional IoT management software.

Local: The bottom tier provides local intelligence, which consists of software running on IoT devices to let them interact with the stratus clouds and with other nodes to deliver scalable IoT services as well as to interact with the whole cloud infrastructure for efficient networking, content delivery, and wireless resource allocation. This last tier consists of elements in the physical environment, such as smartphones, intelligent vehicles, and computers. One example of its functions is intelligently forming ad hoc networks among IoT devices when such networks are needed in situations such as natural disasters.

We're currently working to build a prototype of 3DIA. To succeed, this architecture needs SDN controllers in the global cloud and the stratus clouds to provide networking support. SDN controllers will handle all decisions related to device to device communication -- such as routing, traffic scheduling, and ad hoc vs. Internet communication decisions. Because SDN controllers are daemons/processes running in virtual machines in the cloud, they can be easily scaled up or down and moved between different cloud locations to follow the potentially mobile IoT devices or users. Ideally, IoT scalability could be preserved even for a substantial number of devices.

Questions we can't answer
In my research, there are still questions that we haven't answered.

For example, how can the three architecture tiers function seamlessly across different radio access technologies, while minimizing interference and power consumption?

Can we create smarter ways for devices to spontaneously connect over IoT architectures, so that dynamic IoT services could be created on demand?

How can we share devices concurrently among multiple services while giving priority to real-time services without delaying the others indefinitely?

And how do we handle privacy in a massive IoT, composed of devices belonging to many organizations and individuals?

Though we're still searching for answers to fulfill the proposed vision of the 2020 IoT, where billions of devices are communicating seamlessly and solving many of the inefficiencies of daily life, it's clear that a more intelligent IoT architecture is needed. Our approach is to embed more intelligence in the architecture in the form of cloud resources and software defined networking.

Like the smart cities we hope to enable through IoT, 3DIA can be incrementally deployed over the current Internet. Thus, it could be readily prototyped and widely adopted by industry. We believe this goal is within reach.

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About the Author(s)

Cristian Borcea

Associate Chair, Department of Computer Science, New Jersey Institute of Technology

Cristian Borcea is an Associate Professor and the Associate Chair of the Department of Computer Science at New Jersey Institute of Technology. He is also the program director of the online MS in Computer Science at NJIT ( Cristian also holds a Visiting Associate Professor appointment at the National Institute of Informatics in Tokyo, Japan. His research interests include: mobile computing & sensing; ad hoc & vehicular networks; and cloud & distributed systems. Cristian received his Ph.D. from Rutgers University, and he is a member of ACM, IEEE, and Usenix. 

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