ترغب بنشر مسار تعليمي؟ اضغط هنا

On Practical Aspects of Mobile Data Offloading to Wi-Fi Networks

111   0   0.0 ( 0 )
 نشر من قبل Adnan Aijaz
 تاريخ النشر 2015
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English




اسأل ChatGPT حول البحث

Data traffic over cellular networks is exhibiting an ongoing exponential growth, increasing by an order of magnitude every year and has already surpassed voice traffic. This increase in data traffic demand has led to a need for solutions to enhance capacity provision, whereby traffic offloading to Wi-Fi is one means that can enhance realised capacity. Though offloading to Wi-Fi networks has matured over the years, a number of challenges are still being faced by operators to its realization. In this article, we carry out a survey of the practical challenges faced by operators in data traffic offloading to Wi-Fi networks. We also provide recommendations to successfully address these challenges.



قيم البحث

اقرأ أيضاً

We unveil the existence of a vulnerability in Wi-Fi, which allows an adversary to remotely launch a Denial-of-Service (DoS) attack that propagates both in time and space. This vulnerability stems from a coupling effect induced by hidden nodes. Cascad ing DoS attacks can congest an entire network and do not require the adversary to violate any protocol. We demonstrate the feasibility of such attacks through experiments with real Wi-Fi cards, extensive ns-3 simulations, and theoretical analysis. The simulations show that the attack is effective both in networks operating under fixed and varying bit rates, as well as ad hoc and infrastructure modes. To gain insight into the root-causes of the attack, we model the network as a dynamical system and analyze its limiting behavior. The model predicts that a phase transition (and hence a cascading attack) is possible when the retry limit parameter of Wi-Fi is greater or equal to 7, and explicitly characterizes the phase transition region in terms of the system parameters.
Ultra Reliable Low Latency Communications (URLLC) is an important challenge for the next generation wireless networks, which poses very strict requirements to the delay and packet loss ratio. Satisfaction is hardly possible without introducing additi onal functionality to the existing communication technologies. In the paper, we propose and study an approach to enable URLLC in Wi-Fi networks by exploiting an additional radio similar to that of IEEE 802.11ba. With extensive simulation, we show that our approach allows decreasing the delay by orders of magnitude, while the throughput of non-URLLC devices is reduced insignificantly.
We show experimentally that workload-based AP-STA associations can improve system throughput significantly. We present a predictive model that guides optimal resource allocations in dense Wi-Fi networks and achieves 72-77% of the optimal throughput w ith varying training data set sizes using a 3-day trace of real cable modem traffic.
Time-of-flight, i.e., the time incurred by a signal to travel from transmitter to receiver, is perhaps the most intuitive way to measure distances using wireless signals. It is used in major positioning systems such as GPS, RADAR, and SONAR. However, attempts at using time-of-flight for indoor localization have failed to deliver acceptable accuracy due to fundamental limitations in measuring time on Wi-Fi and other RF consumer technologies. While the research community has developed alternatives for RF-based indoor localization that do not require time-of-flight, those approaches have their own limitations that hamper their use in practice. In particular, many existing approaches need receivers with large antenna arrays while commercial Wi-Fi nodes have two or three antennas. Other systems require fingerprinting the environment to create signal maps. More fundamentally, none of these methods support indoor positioning between a pair of Wi-Fi devices without~third~party~support. In this paper, we present a set of algorithms that measure the time-of-flight to sub-nanosecond accuracy on commercial Wi-Fi cards. We implement these algorithms and demonstrate a system that achieves accurate device-to-device localization, i.e. enables a pair of Wi-Fi devices to locate each other without any support from the infrastructure, not even the location of the access points.
To address 5G challenges, IEEE 802.11 is currently developing new amendments to the Wi-Fi standard, the most promising of which is 802.11ax. A key scenario considered by the developers of this amendment is dense and overlapped networks typically pres ent in residential buildings, offices, airports, stadiums, and other places of a modern city. Being crucial for Wi-Fi hotspots, the hidden station problem becomes even more challenging for dense and overlapped networks, where even access points (APs) can be hidden. In this case, user stations can experience continuous collisions of beacons sent by different APs, which can cause disassociation and break Internet access. In this paper, we show that beacon collisions are rather typical for residential networks and may lead to unexpected and irreproducible malfunction. We investigate how often beacon collisions occur, and describe a number of mechanisms which can be used to avoid beacon collisions in dense deployment. Specifically, we pay much attention to those mechanisms which are currently under consideration of the IEEE 802.11ax group.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا