Futures-Based Resource Trading and Fair Pricing in Real-Time IoT Networks

Abstract

We propose a futures-based resource trading scheme via a forward contract to tackle the risk of trading failure and unfairness associated with the on-site negotiation process in facilitating resource sharing in wireless networks. More specifically, the resource requester and the resource owner negotiate a mutually beneficial forward contract in advance, where the agreement between the two parties are based on the historical statistics related to the resource supply and demand. The risk of trading failure is utilized to determine the contract price and resource amount. Spectrum trading between two different service providers is studied as an example and simulation results show that the proposed futures-based resource trading scheme achieves better performance in terms of success rate and fairness compared with the traditional on-site mechanism.

Unifying Futures and Spot Market: Overbooking-Enabled Resource Trading in Mobile Edge Networks

“…Resource trading mechanism: Existing works devoted to resource trading roughly fall into three categories: i) spot trading (also known as onsite trading), where players reach a trading agreement relying on current conditions (e.g., the current resource demand and supply, channel quality, etc. ), such as online game [13], [14], auction [15]- [17], and bilateral negotiation [18], [19]; ii) futures trading, where players sign a forward contract over buying or selling a certain amount of resources at a predetermined price in advance, that will be fulfilled during each trading in the future, where existing studies mainly investigate electricity market [20]- [22], spectrum resource trading [23], [24], and edge computing-assisted networks [5], [25]; and iii) resource trading in hybrid market where both futures and spot trading are allowed [26], [27]. In [13],…”

“…However, the procedure to reach a trade-related decision usually results in excessive latency and energy consumption [5], [23], [28], which further pose challenges to spot trading players. Take online auction as an example, the winners gain the eventual auction contract while there is no such compensation for the losers who have also spent extra time and energy during decision making.…”

“…Take online auction as an example, the winners gain the eventual auction contract while there is no such compensation for the losers who have also spent extra time and energy during decision making. Moreover, the latency from bidding to practical computing service delivery can greatly impact the quality of experience and the utilization if resources are reserved while waiting for the auction results [5], [8], [23].…”

“…In [22], Morales et al investigated scenario reduction techniques to accurately convey the uncertainties in futures market trading in electricity markets. In spectrum resource trading market, Sheng et al in [23] proposed a futuresbased spectrum trading mechanism to alleviate trading failures, and trading unfairness caused by price fluctuation. In [24], Li et al introduced a futures market to manage the financial risk in spectrum trade and discovering future price.…”

“…To better capture the uncertainty of the wireless communication environment, γ m is applied to describe the varying channel quality between buyer b m and the seller, which represents a continuous random variable obeying an uniform distribution [5], [23] in interval…”