Combining Spot and Futures Markets: A Hybrid Market Approach to Dynamic Spectrum Access

Abstract

Dynamic spectrum access is a new paradigm of secondary spectrum utilization and sharing. It allows unlicensed secondary users (SUs) to exploit opportunistically the under-utilized licensed spectrum. Market mechanism is a widely-used promising means to regulate the consuming behaviours of users and, hence, achieve the efficient allocation and consumption of limited resources. In this paper, we propose and study a hybrid secondary spectrum market consisting of both the futures market and the spot market, in which SUs (buyers) purchase under-utilized licensed spectrum from a spectrum regulator, either through predefined contracts via the futures market, or through spot transactions via the spot market. We focus on the optimal spectrum allocation among SUs in an exogenous hybrid market that maximizes the secondary spectrum utilization efficiency. The problem is challenging due to the stochasticity and asymmetry of network information. To solve this problem, we first derive an off-line optimal allocation policy that maximizes the ex-ante expected spectrum utilization efficiency based on the stochastic distribution of network information. We then propose an on-line VickreyCClarkeCGroves (VCG) auction that determines the real-time allocation and pricing of every spectrum based on the realized network information and the pre-derived off-line policy. We further show that with the spatial frequency reuse, the proposed VCG auction is NP-hard; hence, it is not suitable for on-line implementation, especially in a large-scale market. To this end, we propose a heuristics approach based on an on-line VCG-like mechanism with polynomial-time complexity, and further characterize the corresponding performance loss bound analytically. We finally provide extensive numerical results to evaluate the performance of the proposed solutions.

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],…”

“…Motivated by which, several works also consider the integration of both the futures and spot market. In [26], Gao et al focused on the optimal spectrum allocation among unlicensed secondary users in a hybrid market, which maximized the secondary spectrum utilization efficiency. Vanmechelen et al in [27] proposed a hybrid market in which a low-latency spot market coexists with a higher latency futures market, to deal with the significant delay of the allocation decision procedure of grid resources.…”

Let' s Trade in The Future! A Futures-Enabled Fast Resource Trading Mechanism in Edge Computing-Assisted UAV Networks

“…In [32], Gao et al studied a hybrid secondary spectrum market involving the futures and spot market, where buyers could purchase part of the underutilized licensed spectrum from a spectrum regulator through either predefined contracts or spot transactions. Sheng et al [33] proposed a futures-based spectrum trading mechanism to alleviate the risk of trading failures and unfairness.…”

“…• Case 1 (A > 1): we discuss the following conditions. When x < 1, we have CDF F X (x) = Pr(X ≤ x) = 0; when x > A, we have F X (x) = 1, and Pr(X ≤ x) = 0; when x = A, we have F X (x) = 1, and Pr(X ≤ x) = N −A+1 N ; and when 1 ≤ x < A, we have Pr(X = x) = 1 N , and the relevant F X (x) is calculated as (32).…”

Combining guaranteed and spot markets in display advertising: Selling guaranteed page views with stochastic demand

“…However, their discussion is mainly about the static posted price and they assume that the original values are uniformly distributed and there is no penalty cost. Gao et al (2016) studied a hybrid model that unifies both future and spot markets for dynamic spectrum access, in which buyers can purchase under-utilized licensed spectrum either through predefined contracts or through spot transactions with a VCG-like auction model. Their work is similar to ours, however, the seller does not optimise the contract price dynamically.…”