In this paper, we study contention resolution protocols from a game-theoretic perspective. In a recent work, we considered acknowledgment-based protocols, where a user gets feedback from the channel only when she attempts transmission. In this case she will learn whether her transmission was successful or not. One of the main results of ESA2016 was that no acknowledgment-based protocol can be in equilibrium. In fact, it seems that many natural acknowledgment-based protocols fail to prevent users from unilaterally switching to persistent protocols that always transmit with probability 1. It is therefore natural to ask how powerful a protocol must be so that it can beat persistent deviators. In this paper we consider age-based protocols, which can be described by a sequence of probabilities of transmitting in each time step. Those probabilities are given beforehand and do not change based on the transmission history. We present a 3-player age-based protocol that can prevent users from unilaterally deviating to a persistent protocol in order to decrease their expected transmission time. It is worth noting that the answer to this question does not follow from the results and proof ideas of ESA2016. Our protocol is non-trivial, in the sense that, when all players use it, finite expected transmission time is guaranteed. In fact, we show that this protocol is preferable to any deadline protocol in which, after some fixed time, attempt transmission with probability 1 in every subsequent step. An advantage of our protocol is that it is very simple to describe, and users only need a counter to keep track of time. Whether there exist @math -player age-based protocols that do not use counters and can prevent persistence is left as an open problem for future research.
Perhaps the most famous multiple-access communication protocol is the (slotted) ALOHA protocol @cite_8 @cite_3 . Follow-up papers study the efficiency of multiple-access protocols for packets that are generated by some stochastic process (see e.g. @cite_22 @cite_18 @cite_7 ), or worst-case scenarios of bursty inputs @cite_24 .
@cite_18 @cite_22 @cite_7 @cite_8 @cite_3 @cite_24
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This paper presents the evaluation of the multi-hop aggregate information efficiency of the slotted and unslotted ALOHA protocols. We consider a multi-hop wireless network where the nodes are spatially characterized by a Poisson point process and the traffic generation also follows a Poisson distribution. By applying the properties of stochastic geometry, we derive a closed-form lower bound on the outage probability as a function of the required communication rate, the single-hop distance, the number of hops and the maximum number of retransmissions. The results indicate that slotted ALOHA always outperforms its unslotted version, demonstrating the importance of synchronization in distributed networks. In addition, we show that it is always possible to optimize the network efficiency by properly setting the required rate for a given packet density. Finally, in the scenario considered, the use of retransmissions and multiple hops never achieves the best performance if compared to the option of single-hop links without retransmissions. This paper considers random access protocols with multipacket reception (MPR), which include both slotted-Aloha and slotted τ-persistent CSMA protocols. For both protocols, each node makes a transmission attempt in a slot with a given probability. The goals of this paper are to derive the optimal transmission probability maximizing a system throughput for both protocols and to develop a simple random access protocol with MPR, which achieves a system throughput close to the maximum value. To this end, we first obtain the optimal transmission probability of a node in the slotted-Aloha protocol. The result provides a useful guideline to help us develop a simple distributed algorithm for estimating the number of active nodes. We then obtain the optimal transmission probability in the τ-persistent CSMA protocol. An in-depth study on the relation between the optimal transmission probabilities in both protocols shows that under certain conditions the optimal transmission probability in the slotted-Aloha protocol is a good approximation for the τ-persistent CSMA protocol. Based on this result, we propose a simple τ-persistent CSMA protocol with MPR which dynamically adjusts the transmission probability τ depending on the estimated number of active nodes, and thus can achieve a system throughput close to the maximum value. The multihop spatial reuse Aloha (MSR-Aloha) protocol was recently introduced by Baccelli et aL, where each transmitter selects the receiver among its feasible next hops that maximizes the forward progress of the head of line packet towards its final destination. They identify the optimal medium access probability (MAP) that maximizes the spatial density of progress, defined as the product of the spatial intensity of attempted transmissions times the average per-hop progress of each packet towards its destination. We propose a variant called longest edge routing where each transmitter selects its longest feasible edge, and then identifies a packet in its backlog whose next hop is the associated receiver. The main contribution of this work (and of Baccelli et aL) is the use of stochastic geometry to identify the optimal MAP and the corresponding optimal spatial density of progress. Aloha [1] and its slotted variant [2] are commonly deployed Medium Access Control (MAC) protocols in environments where multiple transmitting devices compete for a medium, yet may have difficulty sensing each others presence. This paper models and evaluates the throughput that can be achieved in a system where nodes compete for bandwidth using a generalized version of slotted- Aloha protocols. We evaluate the channel utilization and fairness of these types of protocols for a variety of node objectives, including maximizing aggregate throughput of the channel, each node greedily maximizing its own throughput, and attacker nodes that attempt to jam the channel. If all nodes are selfish and greedily attempt to maximize their own throughputs, a situation similar to the traditional Prisoners Dilemma[3] arises. Our results reveal that under heavy loads, greedy strategies reduce the utilization, and that attackers cannot do much better than attacking during randomly selected slots.