IBM Researchers find way to make Bitcoin’s Proof-of-Work More Efficient

Scientists at IBM Research claim to have found a new way to make the Bitcoin’s Proof-of-Work (PoW) consensus Protocol to be more efficient in its use of energy without affecting its scalability and security.

Bitcoin has been known to use as much energy as a small country for just running mathematical computations which need to change in order for it to scale.

The R&D arm of IBM published a paper titled ‘Hybrid-IoT: Hybrid Blockchain Architecture for Internet of Things – PoW Sub-blockchains’ where they made comparisons of PoW to The Internet of Things (IoT) which has also evolved into a “decentralized system of cooperating smart objects with the requirement, among others, of achieving distributed consensus.”

They raised the problem that IoT platform solutions are centralized cloud-computing infrastructures and causes problems like high cloud server maintenance costs, issues with supporting time-critical IoT applications, security and trust.

They concluded that by using blockchain technology into IoT can help achieve a proper distributed consensus-based IoT system that overcomes all the above issues. Therefore they adopted Bitcoin’s PoW into Hybrid-IoT (hybrid blockchain architecture for IoT) where subgroups of IoT devices form PoW blockchains, referred to as PoW sub-blockchains. Then, the connection among the PoW sub-blockchains employs a Byzantine Fault Tolerant (BFT) protocol, such as Polkadot or Cosmos, to achieve scalability.

To make things more difficult, IoT devices widely range in their computational power and energy resources as its a broader category which includes everything from a mere temperature sensor to an autonomous internet-connected automobile. With some IoT devices not having the bandwidth to solve much complex PoW computations, there is a need for a better system that focuses on energy efficiency without compromising scalability and security.

The Solution

The team first defined a set of blockchain-IoT integration metrics and tested the design with a simulation framework. They studied the sensitivity of blockchain parameters including blockchain block sizes and block generation intervals, device locations, and the number of peers. The data gathered from these simulations were done on the IBM POWER8 supercomputer that helped frame this problem from the perspective of multi-objective optimization that considered the selection of the sub blockchains subject to scalability, security, peer’s roles, and other integration metrics.

The team examined the results that led to the definition of a set of “sweet spot” guidelines that cluster geographically distributed IoT devices into sub-blockchains, according to preferences made by the user. (e.g., one could give more importance to security or to scalability, and consequently apply different weights to the relevant cost function).

The test was conducted in a geographically distributed framework, in which virtualized IoT devices became peers on Hybrid-IoT with different roles within the different PoW sub blockchain. Thousands of experiments were performed to validate the scalability of the system first, and to check its security on the second step including multiple DDOS and other types of attacks.

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