Network Intrusion Detection Systems (NIDS) and Anti-Denial-of-Service (DoS) employ Deep Packet Inspection (DPI) which provides visibility to the content of payload to detect network attacks. All DPI engines assume a pre-processing step that extracts the various protocol specific fields. However, application layer (L7) field extraction is computationally expensive. We propose a Deep Packet Field Extraction Engine (DPFEE) to offload the application layer field extraction to hardware. DPFEE is a content-aware, grammar-based, Layer 7 programmable field extraction engine for text-based protocols. Our prototype DPFEE implementation for the Session Initiation Protocol (SIP) on a single FPGA, achieved a bandwidth of 257.1 Gbps and this can be easily scaled beyond 300 Gbps.

In today's OFDMA networks, the transmission power is typically fixed and the same for all the sub-carriers that compose a channel. The sub-carriers though, experience different degrees of fading and thus, the received power is different for different sub-carriers; while some frequencies experience deep fades, others are relatively unaffected. In this paper, we make a case for redistributing the power across the sub-carriers (subject to a fixed power budget constraint) to better cope with this frequency selectivity. Specifically, we design a joint power and rate adaptation scheme (called JPRA for short) wherein power redistribution is combined with sub-carrier level rate adaptation to yield significant throughput benefits. We further consider three variants of JPRA: (a) JPRA-Basic where, the power is redistributed across sub-carriers so as to support a maximum common rate across all the sub-carriers (b) JPRA-Intermediate where, the power is redistributed across sub-carriers so as to support a maximum common rate across a “subset” of sub-carriers such that the aggregate rate is maximized. (c) JPRA-Adaptive where, the goal is to redistribute power such that the transmission time of a packet is minimized. While the first two variants decrease transceiver complexity and are simpler, the third is geared towards achieving the maximum throughput possible. We implement all three variants of JPRA on our WARP radio testbed. Our extensive experiments demonstrate that JPRA can provide a 35 percent improvement in total network throughput in testbed experiments compared to FARA, a scheme where only sub-carrier level rate adaptation is used. We also perform simulations to demonstrate the efficacy of JPRA in larger scale networks.

Smartphone based web browsing wastes a lot of power when downloading webpages due to the special characteristics of the 3G radio interface. In this paper, we identify these special characteristics, and address power consumption issues through two novel techniques. First, we reorganize the computation sequence of the web browser when loading a webpage, so that the web browser can first run the computations that will generate new data transmissions and retrieve these data from the web server. Then, the web browser can put the 3G radio interface into low power state, release the radio resource, and then run the remaining computations. Second, we introduce a practical data mining based method to predict the user reading time of webpages, based on which the smartphone can switch to low power state when the reading time is longer than a threshold. To demonstrate the effectiveness of our energy-aware approaches, we develop a testbed with Android phones on T-Mobile UMTS network. Experimental results show that our approach can reduce the power consumption of smartphone by more than 30% during web browsing, and reduce the webpage loading time by 17%.

Vehicular Cyber-Physical Systems (VCPS) provide human drivers with various services related to road safety, and on-road infotainments. Since a service (message) delivery includes service transmission, service display and driver processing, many challenges arise due to limited network resources, possible pre-emption and contention between services for the display and non-negligible driver processing delay. In this paper, we address a new Driver-centric Service Delivery Problem (DSDP) from a cross-disciplinary resource allocation standpoint. Our goal is to deliver a number of services to a set of intended drivers in a given time period so as to maximize the system-wide performance in terms of total utility income (TUI) to drivers. We show that DSDP differs from all existing problems and is NP-Complete. A number of efficient heuristics are proposed to address several issues, including wireless transmission failure as well as distributed implementation of the multi-sender systems. Utilizing real traces collected from taxis in the city of Shanghai, we also present a case study in a more realistic scenario and conduct comprehensive simulations providing numerical results.

We present an analytical framework for modeling a priority-based load balancing scheme in cellular networks based on a new algorithm called direct retry with truncated offloading channel resource pool (DRK). The model, developed for a baseline case of two cell network, differs in many respects from previous works on load balancing. Foremost, it incorporates the call admission process, through random access. In specific, the proposed model implements the Physical Random Access Channel used in 3GPP network standards. Furthermore, the proposed model allows the differentiation of users based on their priorities. The quantitative results illustrate that, for example, cellular network operators can control the manner in which traffic is offloaded between neighboring cells by simply adjusting the length of the random access phase. Our analysis also allows for the quantitative determination of the blocking probability individual users will experience given a specific length of random access phase. Furthermore, we observe that the improvement in blocking probability per shared channel for load balanced users using (DRK) is maximized at an intermediate number of shared channels, as opposed to the maximum number of these shared resources. This occurs because a balance is achieved between the number of users requesting connections and those that are already admitted to the network. We also present an extension of our analytical model to a multicell network (by means of an approximation) and an application of the proposed load balancing scheme in the context of opportunistic spectrum access.

The wide channels feature combines two adjacent channels to form a new, wider channel to facilitate high-data-rate transmissions in multiple-input-multiple-output (MIMO)-based IEEE 802.11n networks. Using a wider channel can exacerbate interference effects. Furthermore, contrary to what has been reported by prior studies, we find that wide channels do not always provide benefits in isolation (i.e., one link without interference) and can even degrade performance. We conduct an in-depth, experimental study to understand the implications of wide channels on throughput performance. Based on our measurements, we design an auto-configuration framework called ACORN for enterprise 802.11n WLANs. ACORN integrates the functions of user association and channel allocation since our study reveals that they are tightly coupled when wide channels are used. We show that the channel allocation problem with the constraints of wide channels is NP-complete. Thus, ACORN uses an algorithm that provides a worst-case approximation ratio of O(1/Δ + 1), with Δ being the maximum node degree in the network. We implement ACORN on our 802.11n testbed. Our evaluations show that ACORN: 1) outperforms previous approaches that are agnostic to wide channels constraints; it provides per-AP throughput gains ranging from 1.5 × 6×; and 2) in practice, its channel allocation module achieves an approximation ratio much better than the theoretically predicted O(1/Δ + 1).

All practical wireless communication systems are prone to errors. At the symbol level, such wireless errors have a well-defined structure: When a receiver decodes a symbol erroneously, it is more likely that the decoded symbol is a good “approximation” of the transmitted symbol than a randomly chosen symbol among all possible transmitted symbols. Based on this property, we define approximate communication, a method that exploits this error structure to natively provide unequal error protection to data bits. Unlike traditional [forward error correction (FEC)-based] mechanisms of unequal error protection that consume additional network and spectrum resources to encode redundant data, the approximate communication technique achieves this property at the PHY layer without consuming any additional network or spectrum resources (apart from a minimal signaling overhead). Approximate communication is particularly useful to media delivery applications that can benefit significantly from unequal error protection of data bits. We show the usefulness of this method to such applications by designing and implementing an end-to-end media delivery system, called Apex. Our Software Defined Radio (SDR)-based experiments reveal that Apex can improve video quality by 5–20 dB [peak signal-to-noise ratio (PSNR)] across a diverse set of wireless conditions when compared to traditional approaches. We believe that mechanisms such as Apex can be a cornerstone in designing future wireless media delivery systems under any error-prone channel condition.

User privacy has been an increasingly growing concern in online social networks (OSNs). While most OSNs today provide some form of privacy controls so that their users can protect their shared content from other users, these controls are typically not sufficiently expressive and/or do not provide fine-grained protection of information. In this paper, we consider the introduction of a new privacy control---group messaging on Twitter, with users having fine-grained control over who can see their messages. Specifically, we demonstrate that such a privacy control can be offered to users of Twitter today without having to wait for Twitter to make changes to its system. We do so by designing and implementing Twitsper, a wrapper around Twitter that enables private group communication among existing Twitter users while preserving Twitter's commercial interests. Our design preserves the privacy of group information (i.e., who communicates with whom) both from the Twitsper server as well as from undesired Twitsper users. Furthermore, our evaluation shows that our implementation of Twitsper imposes minimal server-side bandwidth requirements and incurs low client-side energy consumption. Our Twitsper client for Android-based devices has been downloaded by over 1000 users and its utility has been noted by several media articles.

This paper focuses on routing for vehicles getting access to infrastructure either directly or via multiple hops though other vehicles. We study Routing Protocol for Low power and lossy networks (RPL), a tree-based routing protocol designed for sensor networks. Many design elements from RPL are transferable to the vehicular environment. We provide a simulation performance study of RPL and RPL tuning in VANETs. More specifically, we seek to study the impact of RPL's various parameters and external factors (e.g., various timers and speeds) on its performance and obtain insights on RPL tuning for its use in VANETs.

In this demonstration, we will reveal a full functional wireless access for vehicular environments (WAVE) prototype, which achieves the complete functions defined by the IEEE 802.11p standard through integrating effective and novel base-band algorithms including fast time-synchronization, multiple-stage multiple Doppler detection, accurate channel estimate, and joint QAM demodulation and convolution decoding, all upon the Cyclone III field programmable gate array (FPGA) development kit from the Terasic Company. The WAVE prototype has been extensively tested under various road conditions showing satisfied performances. The WAVE prototype has an Ethernet interface to connect with a computer, upon which media control access (MAC) protocols and a vehicular network simulator operate. Meanwhile, the prototype can also connect with an Acer Iconia Tablet running on the Android system through a universal series bus (USB) to support various intelligent transportation system (ITS) applications based on vehicular communications and networks. This activity is funded by several NSF grants and the CISCO Research Grant.

In this paper, two novel digital signal processing technologies, denoted as polarity-invariant square law (PISL) technology and forgetting factor based successive reference enhancement (SRE) technology, are proposed for transmitted reference (TR) based monobit receivers to compensate the quantization noise and enhance the quality of reference pulses. Since weighted TR (WTR) system can achieve a superior performance as well as a high data-rate under severe multipath environments, the PISL and SRE technologies are applied to the WTR receiver over intra-vehicle channels. The results show that compared to the SRE technology, the PISL technology enables a fixed summation time for all multipath channels, and significantly enhances the performance of the monobit ADC WTR receiver. Therefore, PISL technology is a promising technology to compensate the information loss caused by monobit quantization insuring high-performance, power efficient, and low complexity implementation for TR-based UWB receivers.

High performance and low power consumption have traditionally been the primary design goals for computer architects. With computer systems facing a wave of attacks that disrupt their normal execution or leak sensitive data, computer security is no longer an afterthought. Dynamic integrity checking has emerged as a possible solution to protect computer systems by thwarting various attacks. Dynamic integrity checking involves calculation of hashes of the instructions in the code being executed and comparing these hashes against corresponding precomputed hashes at runtime. The processor pipeline is stalled and the instructions are not allowed to commit until the integrity check is complete. Such an approach has severe performance implications as it stalls the pipeline for several cycles. In this paper, we propose a hardware-based dynamic integrity checking approach that does not stall the processor pipeline. We permit the instructions to commit before the integrity check is complete, and allow them to make changes to the register file, but not the data cache. The system is rolled back to a known state if the checker deems the instructions as modified. Our experiments show an average performance overhead of 1.66%, area overhead of 4.25%, and a power overhead of 2.45% over a baseline processor.

In today's OFDMA networks, the transmission power is typically fixed and the same for all the sub-carriers that compose a channel. The sub-carriers though, experience different degrees of fading and thus, the received power is different for different sub-carriers; while some frequencies experience deep fades, others are relatively unaffected. In this paper, we make a case of redistributing the power across the sub-carriers (subject to a fixed power budget constraint) to better cope with this frequency selectivity. Specifically, we design a joint power and rate adaptation scheme (called JPRA for short) wherein power redistribution is combined with sub-carrier level rate adaptation to yield significant throughput benefits. We further consider two variants of JPRA: (a) JPRA-CR where, the power is redistributed across sub-carriers so as to support a maximum common rate (CR) across sub-carriers and (b) JPRA-MT where, the goal is to redistribute power such that the transmission time of a packet is minimized. While the first variant decreases transceiver complexity and is simpler, the second is geared towards achieving the maximum throughput possible. We implement both variants of JPRA on our WARP radio testbed. Our extensive experiments demonstrate that our scheme provides a 35% improvement in total network throughput in testbed experiments compared to FARA, a scheme where only sub-carrier level rate adaptation is used. We also perform simulations to demonstrate the efficacy of JPRA in larger scale networks.

It is essential to consider drivers' perceptions and reactions when building Vehicular Cyber-Physical Systems (VCPS) since the effectiveness and efficiency of VCPS will largely depend on how drivers could benefit from such a system. This paper considers, for the first time, novel service scheduling problems from a Human Factors (HF) standpoint by taking into consideration the following fact: a driver may not be able to receive more than one service in a short period of time, even if multiple services can be transmitted to the driver from the conventional communications and networking standpoint. We study a family of the HF-aware Service Scheduling (HFSS) Problems, where the goal is to deliver up to n services, each having a time-dependent (and possibly decreasing) utility to a subset of intended drivers so as to minimize the system-wide total utility loss due to unsuccessful delivery of some services. We show that such problems are different from all existing problems. We formulate the basic HFSS problem (BHFSSP) using Integer Linear Programming (ILP) and prove its NP-Completeness. We then propose efficient heuristics for BHFSSP and its more general versions, and present numerical results from large-scale test cases. We also address several practical issues related to wireless transmission failures, distributed implementation in the multisender scenario, and other HF related considerations.

The mmWave communication system is operating at a regime with high number of antennas and very limited number of RF analog chains. Large number of antennas are used to extend the communication range for recovering the high path loss while fewer RF analog chains are designed to reduce transmit and processing power and hardware complexity. In this regime, typical MIMO algorithms are not applicable. Before any communication starts, devices are needed to align their beam pointing angles towards each other. An efficient searching protocol to obtain the best beam angle pair is therefore needed. It is called BeamForming (BF) training protocol. This paper presents a new BF training technique called beam coding. Each beam angle is assigned unique signature code. By coding multiple beam angles and steering at their angles simultaneously in a training packet, the best beam angle pair can be obtained in a few packets. The proposed BF training technique not only shows the robustness in non-line- of-sight environment, but also provides very flat power variation within a packet in contrast to the IEEE 802.11ad standard whose scheme may lead to large dynamic range of signals due to beam angles varying across a training packet.

Network intrusion detection systems continuously monitor the network traffic in order to identify any traces of suspicious activities such as worm, viruses or spam. One attractive technique for identifying potential Internet threats is detecting previously unknown, but common sub-strings that appear very frequently in data packets. In this paper, we propose a novel architectural platform that thoroughly analyzes the network traffic behavior in terms of repetitions to identify potential Internet threats. The main idea is to use a two-phase hashing system and small memory units functioning in parallel to achieve a high-throughput and memory efficient behavioral analysis engine. The system performs behavioral analysis on selected information/user(s) and builds a bell-shaped curve for normal traffic using parallel counters. Our traffic behavioral analysis system has been fully prototyped on Altera Stratix FPGA. Experimental results verify that our system can support line speed of gigabit-rates with very negligible false positive and negative rates.

Channel Bonding (CB) combines two adjacent frequency bands to form a new, wider band to facilitate high data rate transmissions in MIMO-based 802.11n networks. However, the use of a wider band with CB can exacerbate interference effects. Furthermore, CB does not always provide benefits in interference-free settings, and can even degrade performance in some cases. We conduct an in-depth, experimental study to understand the implications of CB. Based on this study we design an auto-configuration framework, ACORN, for enterprise 802.11n WLANs. ACORN integrates the functions of user association and channel allocation, since our study reveals that they are tightly coupled when CB is used. We show that the channel allocation problem with the constraints of CB is NP-complete. Thus, ACORN uses an algorithm that provides a worst case approximation ratio of [EQUATION] with Δ being the maximum node degree in the network. We implement ACORN on our 802.11n testbed. Our experiments show that ACORN (i) outperforms previous approaches that are agnostic to CB constraints; it provides per-AP throughput gains from 1.5x to 6x and (ii) in practice, its channel allocation module achieves an approximation ratio much better than [EQUATION].

We present an analytical framework for modeling a priority-based load balancing scheme in cellular networks. The model differs in many respects from previous work on load balancing, in particular by incorporating the call admission process, through random access; allowing differentiation of users based on their priorities; and by incorporating the received signal properties. The analysis illustrates that, for example, ignoring channel quality has a non- negligible impact on the performance of load balancing. Moreover, the system model allows for the scenario-based determination of whether blocking probability or collision probability (during call admission) is the more dominant factor in the degradation of the performance of UEs affected by load balancing.

Call Admission Control (CAC) is recognized as one of the key strategies to achieve satisfactory QoS support for VoIP over IEEE 802.11 WLANs. However, most of the prior CAC solutions for VoIP over WLAN are centralized, and the few distributed CAC schemes proposed so far do not account for issues such as the loss of channel time due to medium contention and the coexistence of VoIP traffic with background traffic such as TCP data flows. In this paper, we describe a distributed CAC scheme which aims at addressing these issues by leveraging on channel monitoring techniques, thus being readily implementable in today's consumer devices. The proposed scheme is thoroughly evaluated by means of testbed experiments as well as network simulations in different scenarios, and it is shown to yield a better CAC performance with respect to prior solutions.

We present an analytical framework for identifying the most likely number of frequency-hopping transmitters in the presence of potential misdetection. The problem is formulated for the case where there is a single, global misdetection probability characterizing all transmitter/sensor links, and for the case where the misdetection probabilities are permitted to be different across the different pairwise transmitter/sensor links. Simulation results confirm that the approach can lead with high probability to a correct decision regarding the number of interferers.

Nowadays, mobile users wish to use their multi-interface mobile devices to access the Internet through network points of attachment (PoA) based on heterogeneous wireless technologies. They also wish to seamlessly change the PoAs during their ongoing sessions to improve service quality and/or reduce monetary cost. If appropriately handled, multihomed mobile nodes offer a potential solution to this issue. In this paper, we present an improvement of SIP mobility (pre-call plus mid-call mobility) to support seamless mobility of multihomed mobile nodes in heterogeneous wireless networks. Pre-call mobility is extended to associate user identifier (i.e. SIP URI) and interface identifiers (i.e. IP addresses). The multiple addresses of a mobile device are weighted by the user to create a priority list in the SIP server so as to guarantee resilient reachability of mobile nodes and to avoid unnecessary signaling through wireless links, thus saving radio resources. Then, three variations of mid-call mobility, called hard, hybrid and soft procedures, are also proposed. Their main aim is to minimize, or even avoid, packet losses during interface switching at the mobile node. The proposed solutions have been implemented in a wireless heterogeneous testbed composed of 802.11 WLAN plus 3.5 cellular network, which are fully controlled and configurable. The testbed has been used to study the performance and the robustness of the three proposed mid-call mobility procedures.

In this paper we propose network coding to perform multi-hop multicast wireless transmissions. More specifically, we address the problem of reducing redundancy in the completely distributed operation of network coding, so as to increase network throughput. In order to do so, we propose a distributed system where network nodes autonomously make decisions with respect to the packets to encode and forward, with the goal of maximizing the data detection probability and minimizing the overhead of transmitted packets. Our setup consists of a Slotted Aloha network where nodes inject packets at a rate which depends on how useful these packets are to other nodes. We model the selection of transmission probabilities by means of a game theoretic approach, in which nodes reach the desired transmission probabilities as an equilibrium solution to the game. Simulation results show that the proposed scheme outperforms a Slotted Aloha system with optimal uniform retransmission probability.

Characterizing the number and type of transmitters occupying a given frequency band is a critical aspect of spectrum sensing specifically and cognitive radio generally. We present an analytical framework based on probability to identify the number of frequency hopping transmitters of one specific type in a band of interest, and show that the probability mass functions associated with the different potential number of transmitters quickly becomes Gaussian as the number of channel observations increases. Simulation results confirm that the approach can lead with high probability to a correct decision regarding the number of interferers. Thus, the methods here can serve as a valuable complement to other spectrum sensing approaches.