Experimental Results. To compare the actual performance, we implemented the four protocols and compared their costs in this section. We simulated the total computation delay from the time when the membership event happens to the time when group key agreement finishes. Average delay has been measured, since all members do not finish group key agreement simultaneously.
7.2.1 Test Methodology To perform fair comparisons, we consider the followings: – We use and for all measurements. These values are known to be secure in the current technology [23]. – We use 0000-xxx XXX signature with the fixed public exponent 3 for message authentication. All protocols have multiple signature verifications that need to be processed serially. No security risk is known for RSA signatures with small public exponents [11]. – For TGDH, we first generate a random tree by forcing a number of random partition/merge events. Since the cost of TGDH depends on the tree structure, it is fair to generate a random tree instead of a well-balanced or an imbalanced tree. Join We measure the computational delay for a member to join a group of members. (Left graph of Figure 14) In case of TGDH, we use a random tree as described above. The -axis denotes the number of current group members, while the -axis shows the computational delay in seconds. Leave We measure the computational delay for a random member to leave a group of members. (Right graph of Figure 14) Note that the delay for GDH and BD does not depend on the location of the leaving member. However, the number of modular exponentiations for STR upon a leave event depends on the location of the leaving node. For TGDH, we pick a random member from the tree, and measure the average delay for the leave. The -axis denotes the number of remaining group members and the -axis is the computational delay in seconds. Partition We measure the computational delay after a partition. If the number of current group members is and this group shrinks to group of size , we measure the average delay for the remaining group members. For BD and GDH, the location of the leaving members does not matter. However, it is important in STR and TGDH. We, therefore, choose leaving members at random. In Figure 15, the -axis denotes the number of remaining group members. Merge Merge is the trickiest algorithm to measure fairly. First, in BD and GDH, only the number of resulting mem- bers decides the total delay, independent of the number of merging groups. Second, the performance of STR me...
Experimental Results. This section describes the results of evaluating the agreement among the outputs of multiple LVCSR models as an estimate of confi- dence for each hypothesized word. Xxxxxx-SPOJUS Average Precision 98.0 Average Precision 96.8 Average Precision 96.1 Xxxxxx-Xxxxxx SPOJUS-SPOJUS with/without short pause states (Xxxxxx) units in HMMs (Xxxxxx) with/without short pause states (SPOJUS) frame shift lengths (SPOJUS) sampling frequencies (SPOJUS) feature parameters (SPOJUS) duration control / self loop (SPOJUS) 99 98 98 Precision (%) Precision (%) 97 96 95 94 94 93 0 20 40 60 80 100 Order sorted by Precision Order sorted by Precision
Fig. 1: Evaluation Results of Agreement between Two Decoders (Distribution of Precision (%), Newspaper Sentence)
4.1. Agreement between Two Decoders
Experimental Results. Author Manuscript
Experimental Results. To compare the actual performance, we implemented the four protocols and compared their costs in this section. We simulated the total computation delay from the time when the membership event happens to the time when group key agreement finishes. Average delay has been measured, since all members do not finish group key agreement simultaneously.
7.2.1 Test Methodology To perform fair comparisons, we consider the followings: – We use 0000-xxx XXX signature with the fixed public exponent 3 for message authentication. All protocols have multiple signature verifications that need to be processed serially. No security risk is known for RSA signatures with small public exponents [11]. – For TGDH, we first generate a random tree by forcing a number of random partition/merge events. Since the cost of TGDH depends on the tree structure, it is fair to generate a random tree instead of a well-balanced or an imbalanced tree. Merge Merge is the trickiest algorithm to measure fairly. First, in BD and GDH, only the number of resulting mem- bers decides the total delay, independent of the number of merging groups. Second, the performance of STR merge depends on the size of the largest group (which decides the number of modular exponentiation), and the number of groups merging (which determines the number of signature verifications). Finally, the performance of TGDH merge depends upon the number of merging groups (which affects the number of signature generations and verifications), and the key tree structure. The number of current group members is not important for TGDH. Since each protocol has different characteristics, we measured the merge costs as follows: – We assume the maximum number of merging groups is five. In practice, merge of two groups is the most frequent event. However, we allow up to five groups since some group communication systems may allow (require) more than two groups to merge at one time.
Experimental Results. To ensure an accurate comparison between the simulated results and the experimental results, the same state feedback gain K and integral gain Ki were used for experimental testing. The results can be seen in Figure 6 and Figure 7. The system parameters are slightly different from the simulation in that the initial angular position is the stable equilibrium point at 180°. Addi- tionally, the swing up control is used to erect the pendulum in the upright position. The system gain A is shown to be greater than the ±5 Volt saturation cutoff limit of the simulation. The software has been programmed with two terminal voltage saturation points. The first is set to ±7.5 V during swing up, and the second is set to ±5 V once the stabilization controller initiates. This is necessary to achieve a cart driving force great enough to erect the pendulum rod. At the ±5 V limit, the motor is not able to produce enough energy to swing the rod upright. However, using the ±7.5 V limit during stabilization can cause the system to destabilize. Once the swing up controller erected the pendulum, the stabilization controller initiated at roughly 5.5 seconds. After stabilization was achieved a disturbance was introduced to the pendulum rod at about 10 seconds. This disturbance was introduced by ‘tapping’ the pendulum rod in one direction with a force from the hand. Also at roughly 17 sec- onds the linear set point was changed from 0 cm to 25 cm. When viewing the experimental results, there are a number of observa- tions to be made. It is important to note the angular position response of the physical system during swing up. It appears that the angle is cross- ing the 0° threshold on each pass of the cart. This would imply a full revolution of the pendulum rod. However, this is not the case. When viewing the GUI main form, one can see the angular position measure- ment has been set up with 0° at the top, and 180° and -180° both meeting at the bottom of the circle. Due to this configuration, as the pendulum swings through the bottom of the measurement circle the sys- tem interprets this as a full revolution due to the digital filter on the angular position. The calculated motor voltage seen in Figure 7 shows a noisy response. Even with the digital filter added to the output of this calculation, there is a substantial amount of calculation noise present. However, it is important to note the peak values at different times during this test. When a disturbance was introduced at 10 seconds,...
Experimental Results. In the proposed approach a new key management system is used for secure communication. A new member can join and also existing member can get deleted from the group. The keys are updated automatically by using the group member. The keys are distributed before starting the transmissions. Group is created to join the node, sender will encrypt the message and the session key is placed in the header. The receiver will decrypt the key and also the encrypted message. In the receiver side the sender node, transmission times are displayed.
Experimental Results. To verify the effectiveness of the BlendCAC approach against unauthorized access requests, a service access experiment was carried out on a real network environment. In the test scenario, one Raspberry Pi 3 device worked as the client and another worked as the service provider. Given the access authorization process shown in Figure 9a,b, when any of the steps in the authorization procedure failed, the running process immediately aborts instead of continuing to step through all the authorization stages. As shown by Figure 9b, the server stopped the authorization process due to the failure to verify the granted actions or the conditional constraints specified in the access right list. Consequently, the client node received a deny access notification from the server and could not read the requested data. In contrast, Figure 9a presents a successful data request example, in which the whole authorization process was accomplished at the server side without any error, allowing the client to successfully retrieve the data from the service provider. The delegate authorization and revocation results are shown in Figure 9c,f. Figure 9c shows that the delegator ‘0xaa09c6d65908e54bf695748812c51d8f2ceea0f5’ successfully delegated a subset of its delegated permissions to the delegatee ‘0xfa4c5d320d638cbdff557c4c1f3110d3143f40c3’ whose parent was empty. Figure 9d shows a failed delegation scenario caused by assigning permissions to a delegated entity. In the revocation process, only the supervisor or ancestor of the delegatee is allowed to call back the delegated permissions. Figure 9e shows that the delegatee’s parent ‘0xaa09c6d65908e54bf695748812c51d8f2ceea0f5’ was able to successfully revoke the delegation relationship. Otherwise, the delegation revocation request which was from neither the delegatee’s parent ‘0x3d40fad73c91aed74ffbc1f09f4cde7cce533671’ nor any ancestor in delegate path was denied and a failed result is shown in Figure 9f.
Experimental Results. RQ 1. For the first research question, we need to show that we can construct interactive verifiers from automatic verifiers, and that they can be useful in terms of effectiveness. By “interactive verifier”, we mean a verifier that can verify
RQ 2. For the second research question, we need to show that our new design can improve the results of interactive verifiers by annotating invariants that were computed by automatic verifiers. Using our building blocks from Sect. 3, we assemble a construction as illustrated in Fig. 4a (i.e., configurations of the form Witness2ACSL|Verifier). We take a program and a witness and transform the program to a new program that contains the invariants from the witness as ACSL annotations. Let us consider the last row in Table 1: Frama-C is able to prove 20 programs correct using invariants from 31 witnesses. Those 31 witnesses were computed by automatic verifiers, and thus, we can conclude that our new design enables using re- sults of automatic verifiers to help the verification process of an interactive verifier.
RQ 3. For the third research question, we need to show that we can construct result validators from interactive verifiers and that they can effectively complement existing validators. A results validator is a tool that takes as input a verification task, a verdict, and a witness, and confirms or rejects the result. In essence, due to the modular components, the answer to this research question can be given by the same setup as for RQ 2: If the interactive verifier (Frama-C) was able to prove the program correct, then it also has proved that the invariants provided by the witnesses were correct, and thus, the witness should be confirmed. Frama-C has confirmed 31 correctness witnesses.
Experimental Results. After the completion of each blast, a thorough inspection of each column was performed. Crack patterns were observed, and the damage to each column and its respective strengthening system was assessed. Crack sensor measurements were taken both before and after each blast, along with dynamic measurements on Column 1. It should be noted that on the two columns that were strengthened, cracks cannot be observed visually. For these columns, the coaxial cable crack sensors were used to locate cracks after each blast.
Experimental Results. In all experiments we present here we used a single channel of the 3D-DRAM cube connected to the flexible bandwidth and burst length adaption interface of the controller. We considered in our analysis only a single channel to put emphasis on the interface and the power savings per channel. Thus the results can be scaled when multiple channels or slices [17] are used. A single channel allows us also a fair and valid comparison to LPDDR/LPDDR2 devices. However, we had to scale down the applied bandwidth to 750 MB/s for LPDDRx32-333 or LPDDR2x32-667 devices as they support only peak bandwidths up to 1.33 or 2.66 GB/s respectively.
