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Sociality-Aware Access Point Selection in Enterprise Wireless LANs

机译：企业无线局域网中具有社交意识的接入点选择

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摘要

Well-balanced workload among wireless access points (APs) in a wireless local-area network (WLAN) can improve the user experience for accessing the Internet. Most load balancing solutions in WLANs focuses on the optimization of AP operations, assuming that the arrivals and departures of users are independent. However, through the analysis of AP usage based on a real WLAN trace of one-month collected at the Shanghai Jiao Tong University (SJTU), we find that such an assumption does not hold. In fact, due to users' social activities which is particularly time for enterprise environments, they tend to arrive or leave in unison, which would disruptively affect the load balance among APs. In this paper, we propose a novel AP allocation scheme to tackle the load balancing problem in WLANs, taking into account the social relationships of users. In this scheme, users with intense social relationships are assigned to different APs so that jointly departure of those users would have minor impact on the load balance of APs. Given that the problem of allocating an AP for each user so that the average of the sums of social relation intensity between any pair of users in each AP is NP-complete, we propose an online greedy algorithm. Extensive trace-driven simulations demonstrate the efficacy of our scheme. Comparing to the state-of-the-art method, we can achieve about 64.7 percent balancing performance gain on average during peak hours in workdays.
机译：无线局域网（WLAN）中的无线访问点（AP）之间的工作负载均衡，可以改善用户访问Internet的体验。假设用户的到达和离开是独立的，WLAN中的大多数负载平衡解决方案都专注于AP操作的优化。但是，通过基于上海交通大学（SJTU）收集的一个月的真实WLAN跟踪分析AP使用情况，我们发现这种假设不成立。实际上，由于用户的社交活动（特别是在企业环境中的时间），他们往往会统一到达或离开，这会破坏性地影响AP之间的负载平衡。在本文中，我们考虑到用户的社会关系，提出了一种新颖的AP分配方案来解决WLAN中的负载平衡问题。在该方案中，将具有密切社会关系的用户分配给不同的AP，以便这些用户的共同离开对AP的负载平衡影响较小。鉴于为每个用户分配一个AP的问题，使得每个AP中任何一对用户之间的社会关系强度之和的平均值都是NP完全的，我们提出了一种在线贪婪算法。大量跟踪驱动的仿真证明了我们方案的有效性。与最先进的方法相比，我们可以在工作日的高峰时段平均获得约64.7％的平衡性能提升。

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